Systems and Methods for Fluid Delivery

ABSTRACT

A system for at least partial closed-loop control of a medical condition is disclosed. The system includes at least one medical fluid pump. The medical fluid pump including a sensor for determining the volume of fluid pumped by the pump. Also, at least one continuous analyte monitor, and a controller. The controller is in communication with the medical fluid pump and the at least one continuous analyte monitor. The controller includes a processor. The processor includes instructions for delivery of medical fluid based at least on data received from the at least one continuous analyte monitor.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a Non-Provisional Application which claimspriority from U.S. Provisional Patent Application Ser. No. 61/097,021;filed Sep. 15, 2008 and entitled Systems and Methods for Fluid Delivery(F72); U.S. Provisional Patent Application Ser. No. 61/101,053, filedSep. 29, 2008 and entitled Infusion Pump Assembly with a Switch Assembly(F73); U.S. Provisional Patent Application Ser. No. 61/101,077, filedSep. 29, 2008 and entitled Infusion Pump Assembly with Tubing Storage(F74); U.S. Provisional Patent Application Ser. No. 61/101,105, filedSep. 29, 2008 and entitled Improved Infusion Pump Assembly (F75); U.S.Provisional Patent Application Ser. No. 61/101,115, filed Sep. 29, 2008and entitled Filling Apparatus and Methods for an Infusion Pump Assembly(G08); U.S. Provisional Patent Application Ser. No. 61/141,996, filedDec. 31, 2008 and entitled Acoustic Volume Sensing Methods, Systems andApparatus (G07); and U.S. Provisional Patent Application Ser. No.61/141,781, filed Dec. 31, 2008 and entitled Split Ring ResonatorAntenna Adapted for Use in Wirelessly Controlled Medical Device (G81),all of which are hereby incorporated herein by reference in theirentireties.

TECHNICAL FIELD

The present invention relates to the delivery of a fluid and moreparticularly, to systems and methods for fluid delivery.

BACKGROUND INFORMATION

Millions of people live with diabetes mellitus. These patients arefurther commonly classified into one of two types of diabetes, Type Iand Type II. Type I, historically referred to as Juvenile Diabetes, isan autoimmune disease, and is characterized by the inability to secreteinsulin. Type II is a disease that compromises the ability to respond toinsulin and/or produce enough insulin. Both types of diabetes arecharacterized by hyperglycemia. Patient's living with Type I diabetesrequire multiple injections of insulin, a hormone that lowers bloodglucose levels, everyday to survive. However, to maintain long-termhealth people living with diabetes strive to maintain as close to a“non-diabetic” blood glucose level as possible. Maintaining a healthyblood glucose level, however, is a very difficult goal to achieve.

To this end, there have been efforts to design portable devices, e.g.insulin pumps, for the controlled release of insulin. There are manydifferent forms of insulin available. Most patients using an insulinpump currently use U-100 insulin rapid-acting insulin (e.g., HUMALOGinsulin lispro injection or the like) in the pump. Insulin pump devicesare known to have a reservoir such as a cartridge, syringe, or bag, andto be electronically controlled. However, the delivery rates must bemanually entered by the person living with diabetes or a caregiver ofthat person. Thus, the diabetic patient determines/dictates the amountof insulin delivered for any given time/period of time (i.e., the“basal” and “bolus” rate/amount) using information or factors availableto them, for example, their blood glucose readings determined using ablood glucose meter, past data from like situations, the food theyintend to eat or have eaten, anticipated or previously completedexercise, and/or stress or illness.

However, although the diabetic patient determines the rate/amount basedon one or more of these factors (or additional factors), managingdiabetes is not an exact science. There are many reasons for this,including, but not limited to, inaccurate methods of delivery ofinsulin, inaccurate blood glucose meters, inability to correctly countcarbohydrate intake, inability to determine approaching illness,inability to predict the exact effects of exercise, and the inability toanticipate or forecast the effect of many additional hormones orprocesses in the body.

The nature of managing diabetes is further complicated by the risk ofhypoglycemia which may be fatal. Thus, over-calculating the amount ofinsulin required may be life-threatening. Short-term effects ofhyperglycemia are not fatal; however, complications due to long-termhyperglycemia are known and include shorter life span, increased risk ofheart attack or stroke, kidney failure, adult blindness, nerve damageand non-traumatic amputations. Thus, under-calculating the amount ofinsulin required may, in the long-term, substantially affect quality oflife as well as lead to fatal complications.

Accordingly, there is a need for systems and methods for delivering theappropriate amount (i.e., the amount of insulin required to maintain adesired blood glucose level) of insulin at the appropriate time in asafe and effective manner.

SUMMARY

In accordance with one aspect of the present invention, a system for atleast partial closed-loop control of a medical condition. The systemincludes at least one medical fluid pump. The medical fluid pumpincluding a sensor for determining the volume of fluid pumped by thepump. Also, at least one continuous analyte monitor, and a controller.The controller is in communication with the medical fluid pump and theat least one continuous analyte monitor. The controller includes aprocessor. The processor includes instructions for delivery of medicalfluid based at least on data received from the at least one continuousanalyte monitor.

Some embodiments of this aspect of the invention include one or more ofthe following. Where the sensor further includes an acoustic volumesensor. Where the system further includes a network operation center,the network operation center in communication with the processor. Wherethe pump further includes a pumping chamber having an inlet connectableto provide fluid communication with a fluid source, and a pump outletand a force application assembly adapted to provide a compressive stroketo the pumping chamber, wherein the compressive stroke causes arestriction of retrograde flow of fluid from the pumping chamber throughthe inlet while urging fluid from the pumping chamber to the pumpoutlet. Where the force application assembly is coupled to an inletvalve actuator and to a pump actuator, so that the compressive strokeactuates an inlet valve coupled between the inlet and the fluid sourceto close the valve when the pump actuator causes fluid to be urged fromthe pumping chamber to the pump outlet. Where the force applicationassembly comprising a motor for coordinated operation of the valveactuator and the pump actuator, wherein the motor includes at least oneshape-memory actuator. Where at least one of the continuous analytemonitors is a continuous glucose monitor. Where the system includes atleast one accelerometer. Where the system includes at least one bloodoxygen sensor. Where the system further includes at least one inertialmeasurement unit comprising at least one accelerometer and at least onegyroscope. Where the system includes at least one temperature sensor.

In accordance with one aspect of the present invention, a method for atleast partial closed-loop control of a medical condition is disclosed.The method includes receiving glucose data during a time frame or anevent, comparing the glucose data to a previous and similar time frameor event, determining an unexpected result during the time frame or theevent, and sending an alert signal to indicate an unexpected result.

Some embodiments of this aspect of the invention include one or more ofthe following. Wherein sending an alert signal includes alerting a userof the unexpected result. Where the method further includes promptingthe user to enter information regarding the unexpected result. Where thesystem, not receiving information regarding the unexpected result fromthe user, shutting down the system. Wherein shutting down the systemincludes alerting the user of the shutdown through a series of alarms.Wherein alerting the user of the shutdown through a series of alarmsincludes alerting the user of the shutdown through a series ofincreasing alarms.

In accordance with one aspect of the present invention, a method for atleast partial closed-loop control of a medical condition. The methodincludes receiving medical fluid delivery data during a time frame or anevent, comparing the medical fluid delivery data to a previous andsimilar time frame or event, determining an unexpected result during thetime frame or the event, and sending an alert signal to indicate anunexpected result.

Some embodiments of this aspect of the invention include one or more ofthe following. Wherein sending an alert signal includes alerting a userof the unexpected result. Where the method further includes promptingthe user to enter information regarding the unexpected result. Where thesystem, not receiving information regarding the unexpected result fromthe user, shutting down the system. Wherein shutting down the systemincludes alerting the user of the shutdown through a series of alarms.Wherein alerting the user of the shutdown through a series of alarmsincludes alerting the user of the shutdown through a series ofincreasing alarms.

In accordance with one aspect of the present invention, a method formonitoring the integrity of an analyte sensor. The method includesinjecting a volume of an analyte having a predetermined concentration inclose proximity to a continuous analyte sensor for the analyte,receiving data from the continuous analyte sensor, and analyzing thedata to determine whether the analyte sensor is responsive to theinjected volume of analyte.

Some embodiments of this aspect of the invention include wherein theanalyte is glucose.

These aspects of the invention are not meant to be exclusive and otherfeatures, aspects, and advantages of the present invention will bereadily apparent to those of ordinary skill in the art when read inconjunction with the appended claims and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features and advantages of the present invention will bebetter understood by reading the following detailed description, takentogether with the drawings wherein:

FIG. 1 is a diagram of some variables used in diabetes management;

FIG. 2 is a diagram of some variables used in various embodiments of theat least partially closed-loop methods;

FIG. 3 is an illustration of one embodiment of a cannula having depthindicators indicated by different hatch;

FIG. 4 is a graphical representation of an example of a bounded boluspartial close-loop method;

FIG. 5 is a is a graphical representation of an example of a boundedbasal partial close-loop method;

FIG. 6 is an illustration of one embodiment of the system;

FIG. 7 is a side view of an infusion pump assembly;

FIG. 8 is a perspective view of the infusion pump assembly of FIG. 7;

FIG. 9 is an exploded view of various components of the infusion pumpassembly of FIG. 7;

FIG. 10 is a cross-sectional view of the disposable housing assembly ofthe infusion pump assembly of FIG. 7;

FIG. 11 is an isometric view of an alternative embodiment of theinfusion pump assembly of FIG. 7;

FIG. 12 is an plan view of the infusion pump assembly of FIG. 11;

FIG. 13 is a plan view of the infusion pump assembly of FIG. 11;

FIG. 14A is an exploded view of various components of the infusion pumpassembly of FIG. 16;

FIG. 14B is an isometric view of a portion of the infusion pump assemblyof FIG. 11;

FIG. 15 is a cross-sectional view of the disposable housing assembly ofthe infusion pump assembly of FIG. 11;

FIG. 16 is a diagrammatic view of a fluid path within the infusion pumpassembly of FIG. 11;

FIGS. 17A-17C are diagrammatic views of a fluid path within the infusionpump assembly of FIG. 16;

FIG. 18 is an exploded view of various components of the infusion pumpassembly of FIG. 11;

FIG. 19 is a diagrammatic view of a volume sensor assembly includedwithin the infusion pump assembly;

FIG. 20 is a two-dimensional graph of a performance characteristic ofthe volume sensor assembly of FIG. 19;

FIG. 21 is a two-dimensional graph of a performance characteristic ofthe volume sensor assembly of FIG. 19;

FIG. 22 is a two-dimensional graph of a performance characteristic ofthe volume sensor assembly of FIG. 19;

FIG. 23 is a diagrammatic view of a volume sensor assembly includedwithin the infusion pump assembly of FIG. 7;

FIG. 24 is a two-dimensional graph of a performance characteristic ofthe volume sensor assembly of FIG. 23;

FIG. 25 is a two-dimensional graph of a performance characteristic ofthe volume sensor assembly of FIG. 23;

FIG. 26 is a diagrammatic view of a volume sensor assembly includedwithin the infusion pump assembly of FIG. 7;

FIG. 27 is a two-dimensional graph of a performance characteristic of avolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 28 is a two-dimensional graph of a performance characteristic of avolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 29 is a two-dimensional graph of a performance characteristic of avolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 30 is a two-dimensional graph of a performance characteristic of avolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 31 is a two-dimensional graph of a performance characteristic of avolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 32 is a diagrammatic view of a control model for a volume sensorassembly included within the infusion pump assembly of FIG. 7;

FIG. 33 is a diagrammatic view of an electrical control assembly for thevolume sensor assembly included within the infusion pump assembly ofFIG. 7;

FIG. 34 is a diagrammatic view of a volume controller for the volumesensor assembly included within the infusion pump assembly of FIG. 7;

FIG. 35 is a diagrammatic view of a feed forward controller of thevolume controller of FIG. 34;

FIGS. 36-37 diagrammatically depicts an implementation of an SMAcontroller of the volume controller of FIG. 34;

FIG. 38A-38B is an alternate implementation of an SMA controller;

FIG. 39 diagrammatically depicts a multi-processor control configurationthat may be included within the infusion pump assembly of FIG. 7;

FIG. 40 is a diagrammatic view of a multi-processor controlconfiguration that may be included within the infusion pump assembly ofFIG. 7;

FIG. 41A-41B diagrammatically depicts multi-processor functionality;

FIG. 42 diagrammatically depicts multi-processor functionality;

FIG. 43 diagrammatically depicts multi-processor functionality;

FIG. 44 diagrammatically depicts a volume sensor assembly includedwithin the infusion pump assembly of FIG. 7;

FIG. 45 is an exemplary diagram of a split ring resonator antenna;

FIG. 46 is an exemplary diagram of a medical device configured toutilize a split ring resonator antenna;

FIG. 47 is an exemplary diagram of a split ring resonator antenna andtransmission line from a medical infusion device;

FIG. 48 is a graph of the return loss of a split ring resonator antennaprior to contact with human skin;

FIG. 48A is a graph of the return loss of a split ring resonator antennaduring contact with human skin;

FIG. 49 is an exemplary diagram of a split ring resonator antennaintegrated into a device which operates within close proximity todielectric material;

FIG. 50 is a diagram of the dimensions of the inner and outer portion ofthe exemplary embodiment;

FIG. 51 is a graph of the return loss of a non-split ring resonatorantenna prior to contact with human skin;

FIG. 52A is a graph of the return loss of a non-split ring resonatorantenna during contact with human skin.

FIGS. 53A-53B are examples of a basal trajectory and a delivery schedulefor that trajectory;

FIGS. 54A-54B are examples of a basal and extended bolus trajectory anda delivery schedule for that trajectory; and

FIGS. 55A-55B are examples of a basal, extended bolus and normal bolustrajectory and a delivery schedule for that trajectory.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Although insulin and diabetes are discussed herein, this disclosure isnot limited to use of the systems and methods for the treatment ofdiabetes. The disclosed methods and systems may be used for the deliveryof any fluid, including any medical or therapeutic fluid, including butnot limited to, insulin, for the treatment of a medical condition,including, but not limited to, diabetes mellitus.

Described herein are methods and systems for closed loop, or partiallyclosed loop, control of diabetes. As described above, many factorsaffect the amount of insulin a patient or user requires to maintain anappropriate blood glucose level. The term “appropriate” is used hereinto mean a blood glucose level which has been chosen by the patientand/or their health-care provider as healthy for the patient. Theappropriate blood glucose level for each patient may vary, as will theappropriate blood glucose level at any given time for any given patient.In general, many health-care providers recommend maintaining bloodglucose levels between 90-140 mm/dl. However, depending on thecircumstance, the range may vary. For example, a patient may deem ablood glucose level of 150 mg/dl appropriate before bedtime, but wouldconsider the same reading inappropriate before mealtime.

Referring first to FIG. 1, a non-limiting chart of variables used indiabetes management are depicted. These variables shown are thosecurrently taken into consideration by patients living with diabetes.These variables include blood glucose levels, exercise, illness, food,sleep and stress.

Blood glucose levels may be determined by using at least one bloodglucose meter, for example, the FREESTYLE blood glucose meter by AbbottDiabetes Care of Alameda, Calif. Some blood glucose meters maywirelessly transmit the reading to a pump. However, in addition, bloodglucose levels may be determined using at least one continuous glucosemonitor (“CGM”). In the various embodiments, any CGM may be used, forexample, a FREESTYLE NAVIGATOR Continuous Glucose Monitoring System fromAbbott Diabetes Care of Alameda, Calif., or a similar device. Thevarious CGMs include an analyte sensor worn by the patient thattransmits electric signals that correlate to interstitial fluid glucoselevel readings to a handheld or other device at predetermined intervals.

Further, the sensor for the CGM may be any as described in U.S.Published Application No. US-2009-0099522, published Apr. 16, 2009 andentitled Microneedle Systems and Apparatus (G34), which is herebyincorporated herein by reference in its entirety.

Exercise affects people with diabetes differently. Also, depending onthe rigor of the exercise, the type of exercise (i.e., aerobic oranaerobic) and the duration, any given patient will experience differenteffects both during and following the exercise. In some circumstances,blood glucose levels may increase during the exercise, but decreasefollowing the exercise. In some circumstances, the duration and bloodglucose level lowering effect may vary.

Stress may cause elevated blood glucose levels. The duration andintensity of the stress may produce different results. Similarly,illness may cause elevated blood glucose levels, with illness durationand intensity producing various results.

Food includes any item ingested by the patient, including but notlimited to, solids and liquids. The food composition, including fat,protein and carbohydrates, greatly impacts the resulting blood glucoselevel as well as the rate of absorption of the food. The absorption ratemay translate to the rate of increase of blood glucose levels. Forexample, a meal high in fat and carbohydrates may absorb at a slowerrate and thus, the increased levels of blood glucose may be seen at alater time as compared with a meal low in fat. Additionally, withrespect to carbohydrates, the glycemic index of the food will greatlyaffect the rate of change of blood glucose levels.

Various types of insulin may be used either together or individually.Long-acting, intermediate-acting, short-acting and rapid-acting insulinsmay be used. Examples include NPH, Regular, HUMALOG, by Eli Lilly, andNOVALOG, by Novo Nordisk, however, any insulin may be used. Insulins arealso available in various concentrations. For example U-100 and U-400.Various embodiments of the system and methods may use variousconcentrations of insulin.

Insulin and other biologicals/therapeutic and/or medical fluid compoundsare not orally active due to poor absorption, hepatic metabolism orother pharmacokinetic factors. Additionally, some therapeutic compounds,although they may be orally absorbed, are sometimes required to beadministered so often it is difficult for a patient to maintain thedesired schedule. In these cases, parenteral delivery is often employedor could be employed.

Effective parenteral routes of insulin and other fluid drug deliveryinclude subcutaneous injection, intramuscular injection, and intravenous(IV) administration include puncture of the skin with a needle orstylet. Many diabetics prefer an automatic delivery of insulin which ispossible through the use of insulin pumps. These pumps may be used inthe subcutaneous delivery of other fluids as well.

Pumps deliver the therapeutic fluid subcutaneously using a cannula,which is a tube or needle that is introduced to the subcutaneous regionof the skin, and remains in the skin for a pre-approved period of time,typically, no longer than 3 days. The cannula is fluidly connected to areservoir of therapeutic fluid. The pump pumps the fluid from thereservoir to the cannula for delivery to the patient.

Examples of pumps include any pump known, including, but not limited to,those described in U.S. Published Application No. US-2007-0219480,published Sep. 20, 2007 and entitled Patch-Sized Fluid Delivery Systemsand Methods (E72); U.S. Pat. No. 7,306,578, issued Dec. 11, 2007 andentitled Loading Mechanism for Infusion Pump (C54); U.S. Pat. No.7,498,563, issued Mar. 3, 2009 and entitled Optical Displacement Sensorfor Infusion Devices (D78); or U.S. Published Application No.US-2007-0228071, published Oct. 4, 2007 and entitled Fluid DeliverySystems and Methods (E70), which are hereby incorporated herein byreference in their entirety, or other fluid delivery pumps.

Additionally, in some embodiments, a fluid delivery pump that deliversmore than one type of fluid may be used. The pumps described in theaforementioned U.S. Published Application No. US-2007-0219480, publishedSep. 20, 2007 and entitled Patch-Sized Fluid Delivery Systems andMethods (E72); U.S. Pat. No. 7,306,578, issued Dec. 11, 2007 andentitled Loading Mechanism for Infusion Pump (C54); U.S. Pat. No.7,498,563, issued Mar. 3, 2009 and entitled Optical Displacement Sensorfor Infusion Devices (D78); or U.S. Published Application No.US-2007-0228071, published Oct. 4, 2007 and entitled Fluid DeliverySystems and Methods (E70) may be altered slightly to incorporate one ormore additional reservoirs. These reservoirs may be fluidly connected tothe same cannula, or to separate cannulas. Additionally, for all theabove described cannulas, cannulas such as those described in U.S.Published Application No. US-2009-0099522, published Apr. 16, 2009 andentitled Microneedle Systems and Apparatus (G34), which is herebyincorporated herein by reference in its entirety.

The exemplary embodiment includes the use of at least one pump similarto the ones described and shown at least in U.S. Published ApplicationNo. US-2007-0219480, published Sep. 20, 2007 and entitled Patch-SizedFluid Delivery Systems and Methods (E72); U.S. Published Application No.US-2007-0228071, published Oct. 4, 2007 and entitled Fluid DeliverySystems and Methods (E70); U.S. Published Application No.US-2007-0219496, published Sep. 20, 2007 and entitled Pumping FluidDelivery Systems and Methods Using Force Application Assembly (E71);U.S. Published Application No. US-2007-0219597, published Sep. 20, 2007and entitled Adhesive and Peripheral Systems and Methods for MedicalDevices (E73); U.S. patent application Ser. No. 12/347,985, filed Dec.31, 2008 and entitled Infusion Pump Assembly (G75); U.S. patentapplication Ser. No. 12/347,982, filed Dec. 31, 2008 and entitledWearable Pump Assembly (G76); U.S. patent application Ser. No.12/347,981, filed Dec. 31, 2008 and entitled Infusion Pump Assembly(G77); and U.S. patent application Ser. No. 12/347,984, filed Dec. 31,2008 and entitled Pump Assembly With Switch (G79), which are herebyincorporated herein by reference in their entirety.

Specifically, the exemplary embodiment includes a pump having anacoustic volume sensor apparatus capable of measuring the volume offluid pumped by the pump.

In various embodiments, the system includes at least one continuousanalyte sensor, and in some embodiments, at least one continuous glucosemonitor (“CGM”), an infusion pump, fluid pump or medical fluid pump topump at least one medical fluid, e.g., insulin, and a controller. Insome embodiments, the system additionally includes one or moreadditional continuous sensors, whether analyte or other. The systemcomponents transmit data or are controlled by the controller.

Referring now to FIG. 2, the system controller, or the methods ofdetermining fluid delivery volume and timing, takes a number of factorsinto consideration when determining timing volume for dispensing fluids.These factors presented in FIG. 2 are a non-exhaustive list of factorsin which the controller may take into consideration. The system and themethods aim to take data into consideration and deliver insulin or acounter-regulatory to insulin, in response, to maintain a desired bloodglucose level.

The system may use at least one CGM. CGMs include a glucose sensor(referred to as a “sensor” or “analyte sensor”). In various embodiments,the CGM sensor is introduced and remains in the user's interstitialfluid located on the body, e.g., on the abdomen. The CGM sendselectrical signals at predetermined intervals to a receiver orcontroller. The receiver or controller correlates these electric signalsto a glucose value. In some embodiments, redundant CGMs are used toprovide more than one interstitial glucose reading at any given readingtime for safety concerns. In some embodiments, the redundant CGMs may beone or more additional CGMs (the same CGM) located in different parts ofthe patient. In other embodiments, the redundancy may be provided by oneor more sensors integrated onto a single CGM apparatus where all of thesensors are introduced into a similar place on the patient and in someembodiments, using the same auto inserter. In some embodiments, one ormore redundant sensors may be sensors introduced to different depths inthe patient, e.g., if there are 4 redundant sensors, each sensor isintroduced to a different depth in the patient.

Redundant sensors provide additional safety. The sensor readings may besent to a processor which may use various methods to determine if thesystem should accept the reading, or which reading the system shouldaccept, for use in determining the amount of insulin to deliver. Forexample, the processor may determine if the values vary more than 6%,for example (in other embodiments, the percentage different may bedifferent and may be determined and/or specified based one or morecalibration techniques) then the readings may not be used for deliveryand re-calibration (i.e., by a finger-stick) is required. If theprocessor does not receive a signal from one, the processor may beprogrammed to ignore that sensor. If all redundant sensors read the sameor similar value (again, within a percentage that may be pre-programmedor may be pre-determined), then the system may be more confident thevalue is closer to correct.

In some embodiments, the redundant sensors may be calibrateddifferently. For example, one sensor may be calibrated to be moresensitive than the other sensor(s). In some embodiments, the varioussensors are tuned to different dynamic ranges. For example, where twosensors are used, each of the two sensors are tuned to a differentrange, one is tuned to be very sensitive to low blood glucose levels,the other tuned to high blood glucose levels. If for example, the sensortuned low is reading 60 mg/dl, the system will recognize that the sensoris in the patient and reading. If the sensor tuned high is reading 250mg/dl, the system may confirm the sensor is in the patient and reading.In other embodiments, the redundant sensors may be tuned based on atime-constant, i.e., one sensor reads faster than the next, etc.

In some embodiments, a patient may stagger the introduction of one ofmore CGMs such that for any given day, there is always a calibratedsensor providing data to the controller/system. In some embodiments, oneor more CGMs is an implantable CGM.

In various embodiments, the system may include one or more additionalsensors sensing various conditions/health or other analytes of thepatient. The conditions sensed, in the exemplary embodiments, are thoseanalytes or other health indicators that affect the patient's insulinrequirements. The additional sensors may include, but are not limitedto, one or more of the following:

-   -   Heart rate sensor;    -   Analyte sensor for one or more hormones;    -   Thermistor: monitor patient temperature;    -   Temperature sensor: monitor medical fluid temperature;    -   Accelerometers;    -   Gyroscsopes;    -   Inertial Measurement Unit (“IMU”);    -   Respiratory rate monitor;    -   Carbox-symmetry sensor;    -   Galvanic skin;    -   Adrenaline sensor;    -   Oxygen saturation sensor;    -   Hydration sensor;    -   White blood cells count sensor; and/or    -   Signaling hormone sensor.

Additionally, one or more of the sensors, in some embodiments, may beembodied as micro needle-sensors, similar to those described in U.S.Published Application No. US-2009-0099522, published Apr. 16, 2009 andentitled Microneedle Systems and Apparatus (G34), which is herebyincorporated herein by reference in its entirety.

In some embodiments, system may include at least one inertialmeasurement unit (“IMU”). In various embodiments, any type of IMU may beused. In some embodiments, the IMU is a device capable of sensing motionusing a combination of sensors. Various IMUs may include, e.g., one ormore accelerometers and/or one or more gyroscopes, to measureorientation relative to gravity, including, but not limited to, sensingtype, rate, and direction, using a combination of accelerometers and/orgyroscopes. The data collected from the at least one IMU may be used todetermine whether a user is moving. In some embodiments, the datacollected may be used to determine whether a user is sleeping or hasfallen. In other embodiments, the IMU may be used to determine theuser's speed and direction changes, which may indicate the type ofactivity the user is performing, e.g., running, skiing, playing tennis,etc. Thus, at least one IMU may be used to determine the movement of theuser and the data may be collected by the controlled and used by theprocessor.

It should be understood that although the use of at least one IMU fordetermination of movement of a user is described herein, the at leastone IMU may be used in conjunction with any one or more various devicesand/sensors to determine the movement or activity of a user, including,but not limited to, an blood oxygen sensor. In some embodiments, the IMUmay bea MICROSTRAIN® 3DM-GX1® by Microstrain, Inc., Williston, Vt. Insome embodiments, the IMU may be located in the pump or in thecontroller or may be a separate device worn by or on the user. In someembodiments, the IMU used may be a 3-axis IMU including accelerometersand gyropscopes. In some embodiments, the IMU may include 3accelerometers and 3 gyroscopes. These IMUs include output relating topitch, roll and yaw. However, these devices may be large and/or heavyand/or have large power requirements. Thus, it may be desirable, in someembodiments, to use an IMU with including at least one accelerometer andat least one gyroscope.

In some embodiments, one or more, but not limited to, the following maybe used may be used to determine whether a user is exercising orotherwise stressed or experiencing a situation which may change theinsulin sensitivity or insulin requirements: a heart rate monitor,respiratory rate monitor, adrenaline sensor, thermister, and/orhydration sensor. In some embodiments, a hydration sensor may be used todetermine whether a user may be dehydrated, which may contribute tounexpected glucose data. In some embodiments, a temperature sensor maybe used to monitor the temperature of the medical fluid, which mayinclude insulin, which may be used to predict unexpected results oralarm/alert the user when the temperature is higher or lower thanrecommended. In various other embodiments, additional sensors may beused. In various embodiments, one or more sensors may be used and thesesensors may be used on the user, in the pump, and/or in the controllerand/or as a separate device, or in combination thereof.

The controller serves as at least one user interface, and also a centraluser interface for the CGM(s)/sensors, the pump, and thepatient's/user's interface with the control system. For purposes herein,the controller may be programmed by a patient, a “user”, a care-giver, ahealth-care provider or any combination thereof. For purposes of thisdescription however, the term “patient” or “patient/user” or “user”refers to anyone entering information into to controller, or utilizingthe controller to provide care for the patient. In the exemplaryembodiment, the system controller communicates with the various systemcomponents via wireless, e.g., radio frequency (“RF”) communicationand/or other types of remote communication. In the exemplary embodiment,the controller includes a graphical user interface (“GUI”) and one ormore input device, e.g., button(s), capacitive slider(s), jog wheel,touch screen, keypad, electronic keypad, and any other input device. Thecontroller also includes at least one processor, although in theexemplary embodiments, the controller includes at least two processors,a control processor and a safety processor. These processors may beredundant processors, or two different processors providing redundantprocessing or checking the processing of one another.

Some embodiments of the controller may include at least one “event” orspecialty button, e.g., a “food” button, an “exercise” button, and a“bolus” button. In some embodiments, the controller may contain a single“event” button. Pressing or actuating this button may bring the user toan event menu, which may include a list of potential events, one or moreof which may be customizable to the user.

With respect to all event buttons, these buttons, when pressed, wouldbring the patient/user either to a menu or a processing logic thatenables the patient/user to input directly into the processing logic forexercise, food or bolus, for example. The logic may then query thepatient/user to enter additional information, for example, how long theexercise is expected to last, how rigorous, how much food (i.e., how maycarbohydrates), glycemic index, fat content and protein content of thefood. With respect to bolus, the patient/user would be able to input thevolume of a bolus by using a series of button presses or by usinganother input device, i.e., jog wheel, button or slider, to input therequested volume of insulin, i.e., the units of insulin. In someembodiments, the user interface includes many of the same features asfound on insulin pumps and pump controllers known in the art.

In the exemplary embodiment, the controller also includes a “stripreader”, e.g., a space that accepts a glucose test strip for use in“finger stick” or “fingerstick” readings, e.g., the patient pricks theirfingers and uses the blood from the finger to apply to the “fingerstick”. The “strip reader”, using electrochemical testing, determinesthe blood glucose level of the blood. The strip reader may be used tocalibrate the CGM, to double check unexpected or unusual readings, or asa back-up to the CGM in case of CGM failure. In some embodiments, thestrip reader may be a separate device, such as a glucose meter. In theseembodiments, the glucose meter may either wirelessly receive thefingerstick reading or the user may manually input the reading into thecontroller.

The GUI may be a color GUI, a black on gray screen, and/or a touchscreen or other. The GUI may additionally accept and/or give voicecommands and/or provide for magnification on request.

The controller additionally includes at least one speaker and in someembodiments, at least one vibration motor. In some embodiments, thecontroller may include any one or more of the features described in U.S.Published Application No. US-2008-0198012, published Aug. 21, 2008 andentitled Device and Method for Food Management (F21), which is herebyincorporated herein by reference in its entirety.

The controller, in some embodiments, serves as the receiver for the atleast one sensor, including but not limited to, the at least one CGM. Assuch, the user will indicate to the controller when a new sensor isintroduced into the body. In some embodiments, the user may additionallyinput the location of the sensor on the user's body, e.g., whichinclude, but are not limited to, right abdomen, left abdomen, right arm,left arm, right hip, left hip, right left, left leg, etc. This may bedesirable as the sensor may perform differently in different areas onthe body. As the controller will records and process this data, thecontroller may calibrate the sensor based on past profile informationindicating “lag” and/or “drift” information from the same area of thebody.

The medical fluid pump/infusion pump/insulin pump/fluid pump in variousembodiments, is used to deliver medical fluid, which includes insulin,and may include one or more reservoirs for delivery of one or morefluids (thus, the various reservoirs may contain the same fluid ordifferent fluids). In some embodiments, the medical pump may delivermore than one type of insulin (for example, one or more of the typesdescribed above). However, in some embodiments, the medical pumpincluding more than one reservoir may be used to deliver insulin and atleast one counter regulatory hormone, e.g., glucagon. The medical pumpmay be any of the pumps described in U.S. Published Application No.US-2007-0219480, published Sep. 20, 2007 and entitled Patch-Sized FluidDelivery Systems and Methods (E72); U.S. Pat. No. 7,306,578, issued Dec.11, 2007 and entitled Loading Mechanism for Infusion Pump (C54); U.S.Pat. No. 7,498,563, issued Mar. 3, 2009 and entitled OpticalDisplacement Sensor for Infusion Devices (D78); U.S. PublishedApplication No. US-2007-0228071, published Oct. 4, 2007 and entitledFluid Delivery Systems and Methods (E70); U.S. Published Application No.US-2007-0219496, published Sep. 20, 2007 and entitled Pumping FluidDelivery Systems and Methods Using Force Application Assembly (E71);U.S. Published Application No. US-2007-0219597, published Sep. 20, 2007and entitled Adhesive and Peripheral Systems and Methods for MedicalDevices (E73); U.S. patent application Ser. No. 12/347,985, filed Dec.31, 2008 and entitled Infusion Pump Assembly (G75); U.S. patentapplication Ser. No. 12/347,982, filed Dec. 31, 2008 and entitledWearable Pump Assembly (G76); U.S. patent application Ser. No.12/347,981, filed Dec. 31, 2008 and entitled Infusion Pump Assembly(G77); U.S. patent application Ser. No. 12/347,984, filed Dec. 31, 2008and entitled Pump Assembly With Switch (G79); U.S. Published ApplicationNo. US-2009-0099522, published Apr. 16, 2009 and entitled MicroneedleSystems and Apparatus (G34); and U.S. Published Application No.US-2009-0099523, published Apr. 16, 2009 and entitled Infusion PumpAssembly (G46), which are each hereby incorporated herein by referencein their entirety or a modification thereof to accommodate multiplereservoirs.

The system may include one or more alarms, including but not limited to,one or more vibration motors and/or one or more speakers on thecontroller, and in some embodiments, one or more vibrations and/orspeaker motors on the medical pump. Some alarms, in some embodiments,may be progressive alarms, i.e., depending on the alarm type, the alarmprogressively become louder or more aggressive. Alarms may be used toindicate any of a myriad of conditions, including but not limited to:high blood sugar, falling blood sugar or low blood sugar, occlusions,empty or near empty reservoir, system failures, dislodged cannula,dislodged sensor, or any other condition that a patient may wish to beaware.

In some embodiments, the alarm system may further include a signalamplifier separate from the pump and controller. The amplifier mayreceive the alarm signal, and amplify the alarm. The signal amplified,in some embodiments, may be a separate device that may receive wirelesstransmissions from the pump and/or the controller. In some embodiments,the signal amplifier may signal another device to turn on, e.g., a TV ora stereo, automatically trigger a phone to ring, or in some embodiments,where the alarm is not confirmed by the patient/user, the signalamplifier may place a call to an emergency service or an emergencycontact number that is pre-programmed by the patient/user.

In some embodiments, the patient/user may select different types ofalarms for different events/times of day. These selections may bepre-programmed (e.g., every night from 6 pm-6 am, a nighttime alarmsequence will be used if an alarm condition sensed), or may be selectedwhen desired (e.g., before swimming, using a menu, the patient/user mayselect the “swimming alarm”, which may be vibratory only, for example).The controller, in the exemplary embodiment, may be fully programmablewith respect to the alarms such that a patient/user may elect escalatingor progressive alarms for some situations, vibration only for others.Additional alarm conditions that may be programmed by the patient/userinclude but are not limited to the condition required to silence thealarm (for example, a nighttime alarm silence condition may require aseries of inputs to ensure the patient does not turn the alarm off intheir sleep without confirming the condition).

The system may use one or more indicators to determine when one or morecannulas have become dislodged from the patient. In some embodiments, aconductivity sensor may be used to determine if the cannula has becomedislodged from the patient. In some embodiments, the cannual may includea conductive pad around the cannual e.g., a pad including at least twoelectrodes electrically coupled to a central processor. Where thecannula is dislodged, the insulin will be delivered into the pad, thus,changing the conductivity of the pad.

Referring now to FIG. 3, in some embodiments, the cannula used in thesystem may be a cannula including two of more tubing colors serving asvisual indicators of dislodgement. For illustration purposes, the tubingcolors are represented with different hatch marks. For example, the tipof the cannual may be red, the center blue and the end, clear tubing.Thus, the patient may determine, through visual inspection, whether thecannula has become dislodged from the patient.

The system may include one or more integrity tests to determine whetherthe one or more CGM sensors has failed or is providing incorrect orinaccurate information. The terms “incorrect” or “inaccurate”information may be defined as a percentage difference between the CGMreading and a fingerstick reading. The percent difference may refer towhen the CGM reading is either a percentage higher or a percentage lowerthan the fingerstick reading. In some embodiments, any number higherthan e.g. a 30% difference between the fingerstick and the CGM, may betermed “incorrect information” or “inaccurate information”. In otherembodiments, this percentage may be higher of lower than 30%. In someembodiments, this percentage may vary between users and CGM systems.

In some embodiments, a temperature integrity test may be used. Some CGMsensors may experience a drift per degree of temperature shift. Forthese CGM sensors, in some embodiments, where the temperature ismodulated either higher or lower, the system expects a likewisepercentage and/or proportional drift in CGM values. In some embodiments,the system may prompt the user to first, take a fingerstick and then,encounter a temperature shift and take a second fingerstick reading aswell as note the CGM reading. This may provide an integrity test for theCGM. In some embodiments, the system may prompt the user in this way andmay await a temperature shift (which may be determined from atemperature sensor in the pump or controller), then prompt the user totake the second fingerstick. The system may then compare the fingerstickreading to the CGM reading before and after the temperature shift. Ifthe particular CGM, which is expected to experience a shift due totemperature, does not shift, then this may be an indication that theintegrity of the CGM system has been compromised. In these cases, thesystem notifies the user of this error and ceases continuing thesemi-closed or closed loop system of control.

In some embodiments, the system may prompt the user to inject a smallvolume of glucose into an area under the skin, in an area in closeproximity to the CGM sensor. The small volume of glucose may be asolution containing a particular concentration of glucose. The systemmay expect an increase in the glucose readings from the CGM a short timefollowing the injection. In some embodiments, where this same test hasbeen performed on the same user, and where the solution is identical toone used previously, and where the injection was performed in the samemanner, and in the same area in relation to the sensor as previously,the results and profile of the user's response may be in the system andthus, the system may compare the new results to old results or anaverage of old results. If the CGM reading does not indicate thepresence of glucose, or does not match the old results or the average ofthe old results within a margin, then this may be an indication that theintegrity of the CGM system has been compromised. In these cases, thesystem notifies the user of this error and ceases continuing thesemi-closed or closed loop system of control.

In some embodiments, the system may prompt the user to take afingerstick reading on demand. This reading may be used as a systemintegrity check and/or to calibrate the one or more COM sensors. Withrespect to a fingerstick on demand as an integrity check, where thefingerstick reading does not confirm the CGM reading within apercentage, then this may be an indication that the integrity of the CGMsystem has been compromised. In these cases, the system notifies theuser of this error and ceases continuing the semi-closed or closed loopsystem of control. With respect to a fingerstick on demand as acalibration, where the fingerstick reading does not confirm the CGMreading within a percentage, then this may be an indication that theintegrity of the CGM system may have been compromised. The system mayrequest the user enter a second fingerstick to confirm the firstfingerstick reading. After the second fingerstick reading, where thesecond reading confirms the first reading, the system may resume (wherethe reading confirms the CGM integrity) or, where the readings confirmthe integrity may be compromised, the system may notify the user of theerror and cease continuing the semi-closed or closed loop system ofcontrol.

In some embodiments, with respect to the fingerstick on demand, wherethe system requests a fingerstick and the system does not receive afingerstick reading within a predetermined amount of time, e.g., five(5) minutes or ten (10) minutes, the system may default to endclosed-loop or semi-closed loop mode. This provides an additional safetyand also may increase the accuracy of the CGM readings as the system mayrequire, in some embodiments, frequent calibration to assure reliableCGM readings.

With respect to the various integrity tests described herein, in someembodiments, rather than sending a system error or alert, in someembodiments, and in some instances, with any of the integrity checks,the system may determine the percentage difference in the CGM readingsfrom that which is expected and adjust readings accordingly.

In some embodiments, the CGM may provide different or “bad” data when auser is applying pressure to the sensor, e.g., has rolled onto thesensor during sleep. In some embodiments, the system may turn the sensoroff during these times, and may additionally include an indication alerton the controller screen. In some embodiments, when the controllersenses the user is at sleep, the system may shut down, and after acertain amount of elapsed time, e.g., 30 minutes, the system may turnthe sensor on. If the problem/pressure has corrected itself, then thesystem may resume. This may be desirable to allow the user to continuesleeping and perhaps, take the pressure off the sensor on their own,rather than waking them in the night. In some embodiments, during theshut down, delivery of insulin will also stop.

In some embodiments, if after the elapsed time, the system does notcorrect itself, the system will alarm and alert the user that the systemhas shut down.

To manage diabetes using at least a partially closed-loop method, thecomponents of the system described may be used to deliver controlledvolumes of insulin and, in some embodiments, a counter regulatoryhormone, e.g., glucagon, according to a variety of methods, some ofwhich are described herein. In the exemplary embodiments, the controlmethods rely on the use of a system that includes the ability toactively measure the volume of insulin or other fluid that is actuallydelivered to the patient (as opposed to measuring the volume of insulinrequested by the user or pre-programmed by a user to be delivered); atleast one CGM and a user interface and processes containing instructionsfor the at least partial closed loop algorithm. Other sensors and datainput models may also be included, as described in more detail above.However, in some embodiments, pumps that do not actively measure thevolume of insulin or other fluid that the pump is actually delivering tothe patient may also be used. In these embodiments, an assumption ismade that the volume delivered to the patient is the volume requested bythe processor (unless or until a mechanical malfunction or occlusion isdetected).

Referring to FIG. 6 a patient 12 is shown wearing a medical fluid pump14, a sensor apparatus 16 and holding a controller 18. The sensorapparatus 16 may contain one or more CGMs, and one or more additionalsensors. The sensors transmit data to the controller 18. The medicalfluid pump 14 is shown as a patch pump similar to any one of the patchpumps shown and described in U.S. Published Application No.US-2007-0219480, published Sep. 20, 2007 and entitled Patch-Sized FluidDelivery Systems and Methods (E72); U.S. Published Application No.US-2007-0228071, published Oct. 4, 2007 and entitled Fluid DeliverySystems and Methods (E70); U.S. Published Application No.US-2007-0219496, published Sep. 20, 2007 and entitled Pumping FluidDelivery Systems and Methods Using Force Application Assembly (E71);U.S. Published Application No. US-2007-0219597, published Sep. 20, 2007and entitled Adhesive and Peripheral Systems and Methods for MedicalDevices (E73); U.S. patent application Ser. No. 12/347,985, filed Dec.31, 2008 and entitled Infusion Pump Assembly (G75); U.S. patentapplication Ser. No. 12/347,982, filed Dec. 31, 2008 and entitledWearable Pump Assembly (G76); U.S. patent application Ser. No.12/347,981, filed Dec. 31, 2008 and entitled Infusion Pump Assembly(G77); U.S. patent application Ser. No. 12/347,984, filed Dec. 31, 2008and entitled Pump Assembly With Switch (G79); U.S. Published ApplicationNo. US-2009-0099522, published Apr. 16, 2009 and entitled MicroneedleSystems and Apparatus (G34); and U.S. Published Application No.US-2009-0099523, published Apr. 16, 2009 and entitled Infusion PumpAssembly (G46), which are hereby incorporated herein by reference intheir entirety. The patch pump 14 is controlled by the controller(although in some embodiments, may also include a user interfaceallowing for control by the patient/user) and transmits information tothe controller 18. Thus, the controller receives information relating tothe one or more sensors and the pump. The controller additionallyreceives inputs from the user, e.g., events, and may receive manualinputs for fingerstick readings or fingerstick data. Additionally, thecontroller, in some embodiments, may receive information relating tofood or glucose readings, etc., wirelessly. In some embodiments, thecontroller includes voice recognition, thus, in these embodiments, thecontroller may receive commands via voice.

The control methods described herein, in the exemplary embodiments, mayinclude user calibration to the system. User calibration refers tocalibrating the system to the user. This may include, but is not limitedto, collecting CGM data at prescribed times during or following aprescribed event. These may include, but are not limited to, one or moreof the examples given herein.

A prescribed event may include any event the system requests, e.g., afasting event, an exercise event, a meal event, and/or a sleep event.The system may prescribe that a user undergo a “fasting event”. In someembodiments, this includes prompting a user to fast during a certainperiod of time. For example, fasting times may include, but are notlimited to: between midnight and 10 am; between 9 am and 2 pm; between 2pm and 7 pm; and between 7 pm and midnight. These may correlate to amorning fast, a lunch fast, a dinner fast and an overnight fast. Thesystem may take periodic readings during this time to characterize orprofile the user. In some embodiments, the system may require and promptthe user to perform a fingerstick at certain intervals as a verificationof the CGM at this time. These resulting profiles may be used in manyways, including but not limited to: recommending basal setting changes,identifying anomalies, and/or recommending changes in basal boundaries.In some embodiments, the system may recommend or prompt a user tocomplete a fasting profile several times a year, or, as the systemidentifies anomalies in the insulin requirements or in the CGM data, thesystem may prompt the user to complete a fasting profile to eitheridentify a potential problem with either the pump, CGM or controllersystem integrity, or to identify times of day or events where the usermay wish to reconsider boundaries and/or the trajectories or rates, etc.

Other prescribed events may include one or more exercise events. Duringthese events, the user may input the type of exercise being performed.The system may take regular CGM readings and prompt fingerstickverification during the event. Again, as with the fasting events, thesystem may recommend or prompt a user to complete an exercise profileseveral times a year, or, as the system identifies anomalies in theinsulin requirements or in the CGM data, the system may prompt the userto complete an exercise profile to either identify a potential problemwith either the pump, CGM or controller system integrity, or to identifytimes of day or events where the user may wish to reconsider boundariesand/or the trajectories or rates, etc. In some embodiments, the systemmay prompt or the user may request these events. Also, in someembodiments, many different types of exercise events may take place, forexample, but not limited to: anaerobic events, long duration aerobic,short duration anaerobic, long during anaerobic, etc. In this way, theuser may input to the system when they are undertaking any of theseevents and thus, the system may collect additional data that may be usedfor identification of anomalies and/or recommendations to consider theboundaries and/or trajectories during these events.

An eating event may be performed by request from the system or the user.The eating event may be helpful to the user and/or the system toidentify an eating event (where the user fails to input the event intothe system, the system itself may recognize the pattern and prompt theuser with a question, e.g., “are you eating?”). In some embodiments,more than one type of eating events may be captured, for example, theseinclude, but are not limited to: breakfast, lunch, dinner, morningsnack, afternoon snack, and evening snack. In some embodiments, thesystem may request that the user, e.g., “eat a candy bar”. In theseembodiments, the user may select a candy bar and through an input, enterthe information relating to the candy bar into the controller. Then, theuser may elect to begin the requested calibration. The user may eat thecandy bar, and the controller may collect various glucose or other typesof data, during this time. Thus, the system collects a “profile” forthis candy bar, which may be used later either for the same candy bar,and/or for the candy bar at that particular time, under the same orsimilar circumstances. In some embodiments, the system may specify “noexercise” for non-exercise calibration during a calibration day. In someembodiments, the system may specify that the user “exercise” and theneat a particular meal. In each case, the user may interact with thecontroller, inputting various information, including, but not limitedto, the type and/or duration of meal and/or the type and/or duration ofexercise.

In general, patient calibration refers to calibrating the system to anyone or more, but not limited to, of the following: the patient's insulinsensitivity, total reaction time (and kinetic profile) for a giveninsulin in the patient, body fat index, blood glucose profiles forparticular foods or types of foods, blood glucose profiles forparticular exercises (both type/rigor and duration), currentmedications, other diseases and blood glucose profiles for any one ormore, but not limited to, the following: nighttime/sleep, illness,workdays, school days, exam periods, weekends, travel and the like,i.e., for any life-situation in which the patient may experiencefrequently enough the patient (or care-giver, health-care provider)renders it helpful for the system to learn the blood glucose profile forthat experience/situation.

Once the patient calibration for any of the above (or other) iscompleted, the system may be able to identify unexpected results (i.e.,unexpected blood glucose profiles) for any of the calibration types. Insome embodiments, the system may alert the patient that any one or morecalibrations must or should be repeated due to unexpected results.

The patient/user may program a preference for when these alerts, e.g.,pre-program the percentage off from the expected that will trigger analert or any given calibration. Thus, the patient/user may limit alertsand re-calibrations based on particular/pre-set aberrations. Also, thepatient/user may override the alerts. Further, the patient/user mayprefer alerts be triggered where the aberration is 3% during the night,whereas they may prefer 10% during stress.

In some embodiments, the controller may include a menu for calibrationfor various situations. In some embodiments, the patient may have theability to add to the calibration menu, and/or customize the menu. Wherethe patient is experiencing any of the situations, the patient may enterthis information into the controller, thus, the processor/controllerwill know to compare the readings and insulin delivery to thecalibrations. Also, the processor may store the data for each situation,and learn from the data, i.e., adjust the delivery based on this data.

In some embodiments, where there is an unexpected result, the user mayhave the opportunity to explain the aberration/unexpected result. Forexample, if a patient intended to eat a meal, and input this informationinto the system, but failed to eat, e.g., changed their mind or forgot,the system, in reviewing the blood glucose readings, may see that thepatient's blood glucose levels have not risen, as would be expected,thus, this may qualify as an aberration from the expected. The systemmay alert the patient of an aberration, and the patient may input (thrua menu or other) that the intended meal did not take place.

In other embodiments, where the user has not entered an event into thesystem and the system, through CGM or fingerstick data, senses a profilesimilar to an event, or a profile indicating the unexpected results maybe due to a CGM failure, cannula failure, insulin malfunction (e.g.,occlusion, decreased activity due to temperature or age, etc.), thesystem may not changing the volume or schedule of delivery of insulin,rather, the system may prompt the user to enter additional information,e.g., an event, before changing the schedule of insulin delivery. Forexample, if a user does not enter a meal event into the system, and thesystem, through CGM or fingerstick data, senses a blood glucose levelthat is uncharacteristic for the time of day and/or would require thesystem to exceed a preprogrammed basal boundary, the system may alertthe user that there are indications that a greater volume of insulin maybe required to be delivered than is either allowed for that time of day,i.e., the volume may exceed a preprogrammed boundary, or that thedelivery would exceed the maximum volume for the day. In someembodiments, the user may have the opportunity to enter an event oradditional information, within a preprogrammed time from the alert,e.g., within five (5) minutes. The information entered may eitherconfirm the blood glucose data, e.g., based on predetermined profiles,or if the information does not confirm the blood glucose data, theunexpected blood glucose data may be an indication that somethingunexpected and unpredicted has occurred and may alert the user andshut-down the closed-loop or semi-closed loop system. In theseembodiments, if the user fails to provide any information explaining theunexpected blood glucose data, the closed-loop or semi-closed loopsystem may shut-down.

In various embodiments, the closed-loop and/or semi-closed loop systemmay not shut down without first notifying the user, i.e., the systemwill not undergo a silent shut-down, e.g., a shut down without notifyingthe user before shutting down.

In some embodiments, as discussed above, the system may prompt the userto inject a small volume of glucose into an area under the skin, in anarea in close proximity to the CGM sensor. The small volume of glucosemay be a solution containing a particular concentration of glucose. Thesystem may expect an increase in the glucose readings from the CGM ashort time following the injection. In some embodiments, where this sametest has been performed on the same user, and where the solution isidentical to one used previously, and where the injection was performedin the same manner, and in the same area in relation to the sensor aspreviously, the results and profile of the user's response may be in thesystem and thus, the system may compare the new results to old resultsor an average of old results. However, this procedure may additionallybe used in a user calibration process, where the resulting glucoseprofile of the user may be used by the system as a reference of theexpected response from X grams of quick acting carbohydrate in the user.This profile, in some embodiments, may be used to recommend a type ofsnack to the user to treat an anticipated or sensed hypoglycemicepisode.

Various control algorithms may be applied to the at least partiallyclosed-loop system. In some embodiments, the control algorithm(s) thatare applied is patient/user selected. In some embodiments, the variouscontrol algorithms include parameters that are patient selected.

The control algorithms may be turned on or off at any time by thepatient/user. Various algorithms may be used at different times and arepatient driven. Thus, in the exemplary embodiment, the patient/usermaintains control over the use of any given algorithm and that algorithmmay be overridden at any time.

Any one or more of the algorithms described below may be used at anytime. Although some examples of algorithms are discussed below, variousembodiments of the systems described above may be used in conjunctionwith any control algorithm the patient/user desires. Thus, additionalalgorithms may be developed that would be easily integrated onto thecontroller to be used to at least partially control the delivery ofinsulin.

The control algorithms reside, in the exemplary embodiments, on thecontroller. However, in some embodiments, the control algorithms mayreside on the pump, in addition to the controller, or instead of thecontroller. The myriad of control algorithms may be accessed by acontrol system. The control system will receive several patient specificinputs which may be utilized by any control algorithm. These inputsinclude patient calibrations.

In some embodiments, the system includes a network operation center(“NOC”). A NOC may be used to coordinate activities and resources. TheNOC may communicate with the controller and/or the pump via a networkconnection or wirelessly. The NOC being remote from the controller/pumpmay include greater processing power than the controller or pump, thus,may include adaptive software. In some embodiments, the NOC may includeartificial intelligence and/or clinical software. Thus, in theseembodiments, the NOC, rather than the pump or controller (or a user'spersonal computer or “PC”) would host the clinical software. This may bedesirable to prevent software tampering and also, provide a centralpoint for software updates. These updates may be downloaded via anetwork onto the pump and/or controller and/or user's PC.

In some embodiments, the patient/user specifies a “target blood glucosevalue” or a “target blood glucose range” for time ranges or othercharacterized experiences, i.e., including but not limited to one ormore of the following, a target range for exercise, illness, nighttime,pre-meal, post-meal, during meal, etc. These target values may bechanged at any time by the patient/user, based on permissions that aregranted (i.e., in some embodiments, only particular users, i.e., patientand care-giver, have permission or access to change the target values.

Using the data from the one or more sensors, together with the patientcalibration data, the control algorithms serve as methods forcontrolling the delivery of insulin to the patient.

One algorithm that may be utilized is a partial closed-loop algorithm.This refers to an algorithm that provides for closed-loop control of thedelivery of insulin but within a “range” or “set of permissions”. Forexample, referring now to FIG. 4, an embodiment of a “bounded bolus”algorithm is shown. In this embodiment, the user specifies a “boluswindow”, the time in which “bolus” insulin may be requested for deliveryby the controller. Within the specified bolus window, the controllerwill only be allowed, or only has permission to deliver, a particular“bounded” volume of insulin. Taken differently, the bounded bolusalgorithm will prevent delivery of insulin over a particular volumeduring a particular bolus window.

In some embodiments, where the patient/user determines a bolus isrequired, the patient/user may request the “bounded bolus” algorithm,and input the duration and volume permissions.

In some embodiments, the user may specify a “bolus maximum”, which isthe maximum bolus volume, e.g., 15 units, the controller may deliver. Insome embodiments, the user may specify a “24 hour bolus maximum” whichlimits the total volume of bolus insulin delivered during a 24 hoursperiod, e.g., 40 units.

In various embodiments, one or more of these boundaries may be specifiedand preprogrammed by the user. In various embodiments, where thecontroller determines, from the blood glucose values, that a particularvolume should be delivered, but the particular volume exceeds one ormore boundaries, the controller may prompt the user to enter additionalinformation or may shut-down after alerting the user that one or moreboundaries have been met.

Another algorithm that may be utilized is a closed-loop bolus algorithm.This refers to the controller's ability to deliver insulin, based onpatient calibration and input regarding events and targets, at times andat volumes determined by the algorithm. Thus, the closed-loop algorithmwill use the data from the myriad of sensors or other inputs anddetermine the appropriate time and volume for delivery of insulin.

Similar to the partial closed-loop bolus algorithm, described above, thepartial closed-loop basal refers to algorithms that provide forclosed-loop control of the delivery of insulin but within a “range” or“set of permissions”. For example, referring now to FIG. 5, anembodiment of a “bounded bolus” algorithm is shown. In this embodiment,the user specifies a “basal window”, the time in which “basal” insulinmay be requested for delivery by the controller. Within the specifiedbasal window, the controller will only be allowed, or only haspermission to deliver, a particular “bounded” volume of insulin. Takendifferently, the bounded basal algorithm will prevent delivery ofinsulin over a particular volume during a particular basal window. Insome embodiments, the patient/user may have pre-programmed basal rates.In some embodiments, the number of pre-programmed rates may be from1-100. Using the bounded basal algorithm, the patient/user allows thecontroller to change/vary the basal rate for a particular requestedtime-frame, but within pre-programmed parameters. For example, thesystem may be allowed to increase or decrease the basal rate during apre-selected period of time, however, the rate would be “bounded”, i.e.,the system is free to vary the basal rate during the time period butonly within a pre-selected bounded range. The system would not beallowed to deliver at rates higher or lower than the bounded rates forthe pre-selected time period.

In some embodiments of the “bounded” algorithms, the system mayrecommend to the patient/user that the bounded range be extended. Inthese embodiments, the patient/user would have to agree/grant permissionfor the system to deliver beyond the bounded range. In some embodiments,the system may recommend permission to deliver outside the bounded rangefor a single delivery. In other embodiments, the system may recommendpermission to deliver outside the bounded range for a recommended periodof time.

In some embodiments, the user may specify a “basal rate maximum”, whichis the maximum basal rate, e.g., 2 units per hour, the controller maydeliver. In some embodiments, the user may specify a “24 hour basalmaximum” which limits the total volume of basal insulin delivered duringa 24 hours period, e.g., 40 units.

In various embodiments, one or more of these boundaries may be specifiedand preprogrammed by the user. In various embodiments, where thecontroller determines, from the blood glucose values, that a particularvolume should be delivered, but the particular volume exceeds one ormore boundaries, the controller may prompt the user to enter additionalinformation or may shut-down after alerting the user that one or moreboundaries have been met.

Another algorithm that may be utilized is a closed-loop basal algorithm.This refers to the controller's ability to deliver insulin, based onpatient calibration and input regarding events and targets, at times andat volumes determined by the algorithm. Thus, the closed-loop algorithmwill use the data from the myriad of sensors or other inputs anddetermine the appropriate time and volume for delivery of insulin.

Another algorithm is a total closed-loop algorithm. Thus, the system isgiven full control for determining the time and volume of insulindelivery, both for “basal” and “bolus” deliveries. Thus, in someembodiments of this algorithm, the system may not differentiate between“bolus” and “basal” deliveries, rather, the system would deliver insulinbased on patient calibration and data received from the myriad ofpatient sensors. In some embodiments of the closed-loop algorithm, thesystem may also accept user inputs with respect to events/experiencesand take these inputs into consideration when calculating delivery timesand volumes.

In the exemplary embodiments of the systems and methods describedherein, for any algorithm used by the system, where unexpected resultsoccur, the system may automatically shut-down. In some embodiments, thesystem may recommend an auto-shut down, but will require patient/userconfirmation. In other embodiments, the system may employ a method ofauto shut-down that includes notifying the patient/user using a seriesof increasing alarms, and where the system does not receive aconfirmation, will automatically shut-down.

In the exemplary embodiment of the system, the user may pre-program anauto shut-down procedure where the system has not received any inputsfrom the user for a pre-determined interval. For example, where thepatient has not taken a finger stick reading between 6 am-10 am, thesystem may go through the auto-shut down procedure. In the exemplaryembodiments, these pre-programmed auto shut-down procedures and thetime-frames may be specified by the patient/user.

In some embodiments, an auto-shut down procedures may be triggered wherethe finger stick readings and CGM readings vary by a percentage higherthan that which is either acceptable by the system, or pre-programmed bythe patient/user. In some embodiments, similarly, an auto-shut downprocedure may be triggered based on data received from any one or moreof the sensors used in the system.

In various embodiments, the closed-loop and/or semi-closed loop systemdetects anomalies which may include, but are not limited to, unexpectedglucose data and/or unexpected insulin requirements. Either may be anindication that either one or more of the system components is failingor has failed and/or that the user is experiencing or undergoing anunexpected event and/or an unexpected result from an event, e.g.,including, but not limited to, one or more of the following: illness,high carbohydrate meal, long duration meal, long duration exercise, newexercise, and/or stress. In the exemplary embodiments of the semi-closedand/or closed-loop system disclosed herein, the system may shut-downwhen the system detects an anomaly.

In some embodiments, the anomaly may be “good” control. For example, insome embodiments, where the blood glucose data indicates a consistentand/or steady blood glucose reading over multiple readings, this mayindicate that one or more CGM sensors have failed or are failing and/orthat the blood glucose meter has failed. Thus, unexpected glucose datadoes not only refer to unexpectedly “high” or unexpectedly “low”, butrather, may refer to unexpectedly consistent.

Further, in some embodiments, where the glucose data indicates anunexpected hypoglycemic event, this may be an indication that theinsulin pump is experiencing failure or that the user is undergoing anunexpected event (in which case, as discussed above, the system mayprompt the user for further information prior to shutting down).

In some embodiments, where one or more sensors do not confirm either an“event” as indicated by the user or as indicated by the glucose data,this may be an indication that one or more sensors has failed. Thus, asthis is a detected anomaly, the system may shut down.

In some embodiments, where an anomaly is detected, the controller mayprompt the user with a question, e.g., “are you feeling OK?”. Where theuser responds “yes”, the system may confirm that there is a failure andshut-down. Alternately, if the user responds “no”, this may indicatethere is an unexpected event occurring in the user, e.g., stress orillness, and the system may shut-down. In some embodiments, the systemmay prompt the user to enter a fingerstick to confirm the CGM data andin some embodiments, may use the fingerstick data to calibrate the CGMsensor.

In some embodiments, either as an integrity test, or as a calibration,the system may purposely not deliver one or more basal deliveries andrecord the resulting sensor and/or glucose data. This may provide dataindicating the effect on glucose data of each basal delivery which maybe used for optimizing therapy. For example, the system may betteradjust basal based on calibration data from the purposely not delivereddeliveries. This information may also be used to determine insulinsensitivity.

In the exemplary embodiments, where the controller institutes apurposely not delivered delivery, the user may be informed prior to thenon delivered delivery and in some embodiments, the user may be promptedto accept or deny this calibration. In some embodiments, where the userfails to respond within a predetermine amount of time, the system maynot proceed with the calibration.

In some embodiments, the system may perform an insulin sensitivity testby adding or subtracting a percentage of requested basal (either basedon an algorithm or on a trajectory). For example, in some embodiments,the system may subtract or add 10% basal over a duration and record theat least one sensor data. This may be performed regularly, e.g., eachmonth, or during various events, e.g., sleep, exercise, etc. Thesecalibrations are saved and the system may refer back to them todetermine insulin sensitivity or identify a change in insulinsensitivity which may, in some embodiments, prompt the system to requesta calibration to be performed again. Thus, the system creates profilesroutinely, which may be used to identify possible unexpected data whichmay prompt another calibration. In these embodiments, the system isroutinely optimizing the insulin sensitivity factor and basal rates.

In some embodiments, whether a closed-loop control or semi-closed loopcontrol, the system may initialize as an open loop system and in someembodiments, may gradually transition to a closed-loop or semi-closedloop system. In some embodiments, the open loop start-up may be requiredto perform for a predetermined amount of time, e.g., three (3) hours,prior to transitioning to a closed-loop or semi-closed loop system. Insome embodiments, the system may be required to perform a minimum numberof calibrations at start-up prior to the transition.

Once the system is ready for transition, in some embodiments, thetransition may be gradual. In some embodiments, the system may beingdelivery with a preset basal delivery. In some embodiments, the presetbasal delivery may be a percentage, e.g., 10%, 20%, etc., less thanaverage or requested for that user at that time. In some embodiments,the preset basal delivery may start at 50% less than requested, and thenmove to 40%, then 30%, etc., until the rate reaches 0% less. Thus, ateach step, the system may determine whether it is safe to proceed to thenext set based on data from at least one glucose sensor, and in someembodiments, additional sensors and/or fingerstick data.

In some embodiments, the system analyzes the glucose data and determineswhen an excursion has occurred. An excursion may be defined as a glucosereading that is outside the preprogrammed target range. In someembodiments of the system, many different targets may be pre-programmed,either by time or event. An excursion may be defined relative to eitherthe “time” or “event”. For example, during a meal event, it may beexpected that the user's glucose will rise above the pre-meal targetglucose value and then return to a value within the target. Thus, thesystem may include one target definition during the first 120 minutesfollowing a meal bolus and another during from 120-180 minutes followinga meal bolus.

In any case, the system may determine the total amount of time per daythe user spent on “excursion”. This may provide additional data for theuser to re-evaluate one or more of their pre-programmed values,including but not limited to: insulin sensitivity, carbohydrate ratios,targets, and/or boundaries. In some embodiments, the system may includea “grade” or “rating” of the user's glucose levels. The grade or ratingmay be determined by taking into account one or more of the following,including but not limited to: the average glucose level, the totalamount of time spent within target, the total amount of time spent onexcursion, total amount of time the glucose value was changing atgreater than a predetermined rate, and/or the total amount of time spentbelow target. In some embodiments, one or more of these factors may beweighted more heavily in the rating method, e.g., total amount of timespent on excursion may be weighted more heavily than the total amount oftime spent below target. In some embodiments, the grade or rating may bedetermined by weighing more heavily the total amount of time spent aboveor below the target. In some embodiments, the total amount of time theglucose value was changing at greater than a predetermined rate may beweighed more heavily than other factors.

In some embodiments, the average glucose levels may be correlated to a“predicted” A1C level. For example, if a user has an average glucosevalue of 135 mg/dl over the past 90 days, the system may indicate to theuser that this likely translates to an A1C level of 6.0%.

As discussed above, various embodiments of the system may include one ormore of the various infusion pumps incorporated herein by reference.Below is a description of some embodiments of the infusion pump whichmay be used in some embodiments of the system.

Referring to FIGS. 7-9, an infusion pump assembly 100 may include areusable housing assembly 102. Reusable housing assembly 102 may beconstructed from any suitable material, such as a hard or rigid plastic,that will resist compression. For example, use of durable materials andparts may improve quality and reduce costs by providing a reusableportion that lasts longer and is more durable, providing greaterprotection to components disposed therein.

Reusable housing assembly 102 may include mechanical control assembly104 having a pump assembly 106 and at least one valve assembly 108.Reusable housing assembly 102 may also include electrical controlassembly 110 configured to provide one or more control signals tomechanical control assembly 104 and effectuate the basal and/or bolusdelivery of an infusible fluid to a user. Disposable housing assembly114 may include valve assembly 108 which, may be configured to controlthe flow of the infusible fluid through a fluid path. Reusable housingassembly 102 may also include pump assembly 106 which may be configuredto pump the infusible fluid from the fluid path to the user.

Electrical control assembly 110 may monitor and control the amount ofinfusible fluid that has been and/or is being pumped. For example,electrical control assembly 110 may receive signals from volume sensorassembly 148 and calculate the amount of infusible fluid that has justbeen dispensed and determine, based upon the dosage required by theuser, whether enough infusible fluid has been dispensed. If enoughinfusible fluid has not been dispensed, electrical control assembly 110may determine that more infusible fluid should be pumped. Electricalcontrol assembly 110 may provide the appropriate signal to mechanicalcontrol assembly 104 so that any additional necessary dosage may bepumped or electrical control assembly 110 may provide the appropriatesignal to mechanical control assembly 104 so that the additional dosagemay be dispensed with the next dosage. Alternatively, if too muchinfusible fluid has been dispensed, electrical control assembly 110 mayprovide the appropriate signal to mechanical control assembly 104 sothat less infusible fluid may be dispensed in the next dosage.

Mechanical control assembly 104 may include at least one shape-memoryactuator 112. Pump assembly 106 and/or valve assembly 108 of mechanicalcontrol assembly 104 may be actuated by at least one shape-memoryactuator, e.g., shape-memory actuator 112, which may be a shape-memorywire in wire or spring configuration. Shape memory actuator 112 may beoperably connected to and activated by electrical control assembly 110,which may control the timing and the amount of heat and/or electricalenergy used to actuate mechanical control assembly 104. Shape memoryactuator 112 may be, for example, a conductive shape-memory alloy wirethat changes shape with temperature. The temperature of shape-memoryactuator 112 may be changed with a heater, or more conveniently, byapplication of electrical energy. Shape memory actuator 112 may be ashape memory wire constructed of nickel/titanium alloy, such as NITINOL™or FLEXINOL®.

Infusion pump assembly 100 may include a volume sensor assembly 148configured to monitor the amount of fluid infused by infusion pumpassembly 100. For example, volume sensor assembly 148 may employ, forexample, acoustic volume sensing. Acoustic volume measurement technologyis the subject of U.S. Pat. Nos. 5,575,310 and 5,755,683 assigned toDEKA Products Limited Partnership, as well as U.S. patent applicationPublication Nos. US 2007/0228071 A1, US 2007/0219496 A1, US 2007/0219480A1, US 2007/0219597 A1, the entire disclosures of all of which areincorporated herein by reference. Other alternative techniques formeasuring fluid flow may also be used; for example, Doppler-basedmethods; the use of Hall-effect sensors in combination with a vane orflapper valve; the use of a strain beam (for example, related to aflexible member over a fluid reservoir to sense deflection of theflexible member); the use of capacitive sensing with plates; or thermaltime of flight methods. One such alternative technique is disclosed inU.S. patent application Ser. No. 11/704,899, entitled Fluid DeliverySystems and Methods, filed 9 Feb. 2007, the entire disclosure of whichis incorporated herein by reference. Infusion pump assembly 100 may beconfigured so that the volume measurements produced by volume sensorassembly 148 may be used to control, through a feedback loop, the amountof infusible fluid that is infused into the user.

Infusion pump assembly 100 may further include a disposable housingassembly 114. For example, disposable housing assembly 114 may beconfigured for a single use or for use for a specified period of time,e.g., three days or any other amount of time. Disposable housingassembly 114 may be configured such that any components in infusion pumpassembly 100 that come in contact with the infusible fluid are disposedon and/or within disposable housing assembly 114. For example, a fluidpath or channel including a reservoir, may be positioned withindisposable housing assembly 114 and may be configured for a single useor for a specified number of uses before disposal. The disposable natureof disposable housing assembly 114 may improve sanitation of infusionpump assembly 100.

Referring also to FIG. 10, disposable housing assembly 114 may beconfigured to releasably engage reusable housing assembly 102, andincludes a cavity 116 that has a reservoir 118 for receiving aninfusible fluid (not shown), e.g., insulin. Such releasable engagementmay be accomplished by a screw-on, a twist-lock or a compression fitconfiguration, for example. Disposable housing assembly 114 and/orreusable housing assembly 102 may include an alignment assemblyconfigured to assist in aligning disposable housing assembly 114 andreusable housing assembly 102 for engagement in a specific orientation.Similarly, base nub 120 and top nub 122 may be used as indicators ofalignment and complete engagement.

Cavity 116 may be at least partially formed by and integral todisposable housing assembly 114. Cavity 116 may include a membraneassembly 124 for at least partially defining reservoir 118. Reservoir118 may be further defined by disposable housing assembly 114, e.g., bya recess 126 formed in base portion 128 of disposable housing assembly114. For example, membrane assembly 124 may be disposed over recess 126and attached to base portion 128, thereby forming reservoir 118.Membrane assembly 124 may be attached to base portion 128 byconventional means, such as gluing, heat sealing, and/or compressionfitting, such that a seal 130 is formed between membrane assembly 124and base portion 128. Membrane assembly 124 may be flexible and thespace formed between membrane assembly 124 and recess 126 in baseportion 128 may define reservoir 118. Reservoir 118 may benon-pressurized and in fluid communication with a fluid path (notshown). Membrane assembly 124 may be at least partially collapsible andcavity 116 may include a vent assembly, thereby advantageouslypreventing the buildup of a vacuum in reservoir 118 as the infusiblefluid is delivered from reservoir 118 to the fluid path. In a preferredembodiment, membrane assembly 124 is fully collapsible, thus allowingfor the complete delivery of the infusible fluid. Cavity 116 may beconfigured to provide sufficient space to ensure there is always someair space even when reservoir 118 is filled with infusible fluid.

The membranes and reservoirs described herein may be made from materialsincluding but not limited to silicone, NITRILE, and any other materialhaving desired resilience and properties for functioning as describedherein. Additionally, other structures could serve the same purpose.

The use of a partially collapsible non pressurized reservoir mayadvantageously prevent the buildup of air in the reservoir as the fluidin the reservoir is depleted. Air buildup in a vented reservoir couldprevent fluid egress from the reservoir, especially if the system istilted so that an air pocket intervenes between the fluid contained inthe reservoir and the septum of the reservoir. Tilting of the system isexpected during normal operation as a wearable device.

Reservoir 118 may be conveniently sized to hold an insulin supplysufficient for delivery over one or more days. For example, reservoir118 may hold about 1.00 to 3.00 ml of insulin. A 3.00 ml insulinreservoir may correspond to approximately a three day supply for about90% of potential users. In other embodiments, reservoir 118 may be anysize or shape and may be adapted to hold any amount of insulin or otherinfusible fluid. In some embodiments, the size and shape of cavity 116and reservoir 118 is related to the type of infusible fluid that cavity116 and reservoir 118 are adapted to hold.

Disposable housing assembly 114 may include a support member 132 (FIG.9) configured to prevent accidental compression of reservoir 118.Compression of reservoir 118 may result in an unintentional dosage ofinfusible fluid being forced through the fluid path to the user. In apreferred embodiment, reusable housing assembly 102 and disposablehousing assembly 114 may be constructed of a rigid material that is noteasily compressible. However, as an added precaution, support member 132may be included within disposable housing assembly 114 to preventcompression of infusion pump assembly 100 and cavity 116 therein.Support member 132 may be a rigid projection from base portion 128. Forexample, support member 132 may be disposed within cavity 116 and mayprevent compression of reservoir 118.

As discussed above, cavity 116 may be configured to provide sufficientspace to ensure there is always some air space even when reservoir 118is filled with infusible fluid. Accordingly, in the event that infusionpump assembly 100 is accidentally compressed, the infusible fluid maynot be forced through cannula assembly 136.

Cavity 116 may include a septum assembly 146 (FIG. 9) configured toallow reservoir 118 to be filled with the infusible fluid. Septumassembly 146 may be a conventional septum made from rubber or plasticand have a one-way fluid valve configured to allow a user to fillreservoir 118 from a syringe or other filling device. In someembodiments, septum 146 may be located on the top of membrane assembly124. In these embodiments, cavity 116 may include a support structure(e.g., support member 132 in FIG. 9) for supporting the area about theback side of the septum so as to maintain the integrity of the septumseal when a needle is introducing infusible fluid into cavity 116. Thesupport structure may be configured to support the septum while stillallowing the introduction of the needle for introducing infusible fluidinto cavity 116.

Infusion pump assembly 100 may include an overfill prevention assembly(not shown) that may e.g., protrude into cavity 116 and may e.g.,prevent the overfilling of reservoir 118.

Referring also to FIGS. 11-13, there is shown an alternative-embodimentinfusion pump assembly 500. As with pump assembly 100, 100′, infusionpump assembly 500 may include reusable housing assembly 502 anddisposable housing assembly 504.

In a fashion similar to reusable housing assembly 402, reusable housingassembly 502 may include a mechanical control assembly (that includes atleast one pump assembly and at least one valve assembly). Reusablehousing assembly 502 may also include an electrical control assemblythat is configured to provide control signals to the mechanical controlassembly and effectuate the delivery of an infusible fluid to a user.The valve assembly may be configured to control the flow of theinfusible fluid through a fluid path and the pump assembly may beconfigured to pump the infusible fluid from the fluid path to the user

In a fashion similar to disposable housing assembly 404, disposablehousing assembly 504 may be configured for a single use or for use for aspecified period of time, e.g., e.g., three days or any other amount oftime. Disposable housing assembly 504 may be configured such that anycomponents in infusion pump assembly 500 that come in contact with theinfusible fluid are disposed on and/or within disposable housingassembly 504.

In this particular embodiment of the infusion pump assembly, infusionpump assembly 500 may include switch assembly 506 positioned about theperiphery of infusion pump assembly 500. For example, switch assembly506 may be positioned along a radial edge of infusion pump assembly 500,which may allow for easier use by a user. Switch assembly 506 may becovered with a waterproof membrane and/or an o-ring or other sealingmechanism may be included on the stem 507 of the switch assembly 506configured to prevent the infiltration of water into infusion pumpassembly 500. However, in some embodiments, switch assembly 506 mayinclude an overmolded rubber button, thus providing functionality as awaterproof seal without the use of a waterproof membrane or an o-ring.However, in still other embodiments, the overmolded rubber button mayadditionally be covered by a waterproof membrane and/or include ano-ring. Reusable housing assembly 502 may include main body portion 508(housing the above-described mechanical and electrical controlassemblies) and locking ring assembly 510 that may be configured torotate about main body portion 508 (in the direction of arrow 512).

In a fashion similar to reusable housing assembly 402 and disposablehousing assembly 404, reusable housing assembly 502 may be configured toreleasably engage disposable housing assembly 504. Such releasableengagement may be accomplished by a screw-on, a twist-lock or acompression fit configuration, for example. In an embodiment in which atwist-lock configuration is utilized, the user of infusion pump assembly500 may first properly position reusable housing assembly 502 withrespect to disposable housing assembly 504 and may then rotate lockingring assembly 510 (in the direction of arrow 512) to releasably engagereusable housing assembly 502 with disposable housing assembly 404.

As locking ring assembly 510 included within infusion pump assembly 500may be taller (i.e., as indicated by arrow 514) than locking ringassembly 410, locking ring assembly 510 may include a passage 516through which button 506 may pass. Accordingly, when assembling reusablehousing assembly 502, locking ring assembly 510 may be installed ontomain body portion 508 (in the direction of arrow 518). Once locking ringassembly 510 is installed onto main body portion 508, one or morelocking tabs (not shown) may prevent locking ring assembly 510 frombeing removed from main body portion 508. The portion of switch assembly506 that protrudes through passage 516 may then be pressed into mainbody portion 508 (in the direction of arrow 520), thus completing theinstallation of switch assembly 506.

Although button 506 is shown in various locations on infusion pumpassembly 500, button 506, in other embodiments, may be located anywheredesirable on infusion pump assembly 500.

Through the use of locking ring assembly 510, reusable housing assembly502 may be properly positioned with respect to disposable housingassembly 504 and then releasably engaged by rotating locking ringassembly 510, thus eliminating the need to rotate reusable housingassembly 502 with respect to disposable housing assembly 504.Accordingly, reusable housing assembly 502 may be properly aligned withdisposable housing assembly 504 prior to engagement, and such alignmentmay not be disturbed during the engagement process. Locking ringassembly 510 may include a latching mechanism (not shown) that preventsthe rotation of locking ring assembly 510 until reusable housingassembly 502 and disposable housing assembly 504 are properly positionedwith respect to each other. Passage 516 may be elongated to allow forthe movement of locking ring 510 about switch assembly 506.

Referring also to FIGS. 14A-14B & 15-16, there are shown various viewsof infusion pump assembly 500, which is shown to include reusablehousing assembly 502, switch assembly 506, and main body portion 508. Asdiscussed above, main body portion 508 may include a plurality ofcomponents, examples of which may include but are not limited to volumesensor assembly 148, printed circuit board 600, vibration motor assembly602, shape memory actuator anchor 604, switch assembly 506, battery 606,antenna assembly 608, pump assembly 106, measurement valve assembly 610,volume sensor valve assembly 612 and reservoir valve assembly 614. Toenhance clarity, printed circuit board 600 has been removed from FIG.14B to allow for viewing of the various components positioned beneathprinted circuit board 600.

The various electrical components that may be electrically coupled withprinted circuit board 600 may utilize spring-biased terminals that allowfor electrical coupling without the need for soldering the connections.For example, vibration motor assembly 602 may utilize a pair ofspring-biased terminals (one positive terminal and one negativeterminal) that are configured to press against corresponding conductivepads on printed circuit board 600 when vibration motor assembly 602 ispositioned on printed circuit board 600. However, in the exemplaryembodiment, vibration motor assembly 602 is soldered directly to theprinted circuit board.

As discussed above, volume sensor assembly 148 may be configured tomonitor the amount of fluid infused by infusion pump assembly 500. Forexample, volume sensor assembly 148 may employ acoustic volume sensing,which is the subject of U.S. Pat. Nos. 5,575,310 and 5,755,683 assignedto DEKA Products Limited Partnership, as well as the U.S. patentapplication Publication Nos. US 2007/0228071 A1, US 2007/0219496 A1, US2007/0219480 A1, US 2007/0219597 A1, the entire disclosures of all ofwhich are incorporated herein by reference.

Vibration motor assembly 602 may be configured to provide avibration-based signal to the user of infusion pump assembly 500. Forexample, in the event that the voltage of battery 606 (which powersinfusion pump assembly 500) is below the minimum acceptable voltage,vibration motor assembly 602 may vibrate infusion pump assembly 500 toprovide a vibration-based signal to the user of infusion pump assembly500. Shape memory actuator anchor 604 may provide a mounting point forthe above-described shape memory actuator (e.g. shape memory actuator112). As discussed above, shape memory actuator 112 may be, for example,a conductive shape-memory alloy wire that changes shape withtemperature. The temperature of shape-memory actuator 112 may be changedwith a heater, or more conveniently, by application of electricalenergy. Accordingly, one end of shape memory actuator 112 may be rigidlyaffixed (i.e., anchored) to shape memory actuator anchor 604 and theother end of shape memory actuator 112 may be applied to e.g. a valveassembly and/or a pump actuator. Therefore, by applying electricalenergy to shape memory actuator 112, the length of shape memory actuator112 may be controlled and, therefore, the valve assembly and/or the pumpactuator to which it is attached may be manipulated.

Antenna assembly 608 may be configured to allow for wirelesscommunication between e.g. infusion pump assembly 500 and a remotecontrol assembly. As discussed above, the remote control assembly mayallow the user to program infusion pump assembly 500 and e.g. configurebolus infusion events. As discussed above, infusion pump assembly 500may include one or more valve assemblies configured to control the flowof the infusible fluid through a fluid path (within infusion pumpassembly 500) and pump assembly 106 may be configured to pump theinfusible fluid from the fluid path to the user. In this particularembodiment of infusion pump assembly 500, infusion pump assembly 500 isshown to include three valve assemblies, namely measurement valveassembly 610, volume sensor valve assembly 612, and reservoir valveassembly 614.

As discussed above and referring also to FIG. 16, the infusible fluidmay be stored within reservoir 118. In order to effectuate the deliveryof the infusible fluid to the user, the processing logic (not shown)included within infusion pump assembly 500 may energize shape memoryactuator 112, which may be anchored on one end using shape memoryactuator anchor 604. Referring also to FIG. 17A, shape memory actuator112 may result in the activation of pump assembly 106 and reservoirvalve assembly 614. Reservoir valve assembly 614 may include reservoirvalve actuator 614A and reservoir valve 614B, and the activation ofreservoir valve assembly 614 may result in the downward displacement ofreservoir valve actuator 614A and the closing of reservoir valve 614B,resulting in the effective isolation of reservoir 118. Further, pumpassembly 106 may include pump plunger 106A and pump chamber 106B and theactivation of pump assembly 106 may result in pump plunger 106A beingdisplaced in a downward fashion into pump chamber 106B and thedisplacement of the infusible fluid (in the direction of arrow 616).

Volume sensor valve assembly 612 may include volume sensor valveactuator 612A and volume sensor valve 612B. Referring also to FIG. 17B,volume sensor valve actuator 612A may be closed via a spring assemblythat provides mechanical force to seal volume sensor valve 612B.However, when pump assembly 106 is activated, if the displaced infusiblefluid is of sufficient pressure to overcome the mechanical sealing forceof volume sensor valve assembly 612, the displacement of the infusiblefluid occurs in the direction of arrow 618. This may result in thefilling of volume sensor chamber 620 included within volume sensorassembly 148. Through the use of speaker assembly 622, port assembly624, reference microphone 626, spring diaphragm 628, invariable volumemicrophone 630, volume sensor assembly 148 may determine the volume ofinfusible fluid included within volume sensor chamber 620.

Referring also to FIG. 17C, once the volume of infusible fluid includedwithin volume sensor chamber 620 is calculated, shape memory actuator632 may be energized, resulting in the activation of measurement valveassembly 610, which may include measurement valve actuator 610A andmeasurement valve 610B. Once activated and due to the mechanical energyasserted on the infusible fluid within volume sensor chamber 620 byspring diaphragm 628, the infusible fluid within volume sensor chamber620 may be displaced (in the direction of arrow 634) through disposablecannula 138 and into the body of the user.

Referring also to FIG. 18, there is shown an exploded view of infusionpump assembly 500. Shape memory actuator 632 may be anchored (on a firstend) to shape memory actuator anchor 636. Additionally, the other end ofshape memory actuator 632 may be used to provide mechanical energy tovalve assembly 638, which may activate measurement valve assembly 610.Volume sensor assembly spring retainer 642 may properly position volumesensor assembly 148 with respect to the various other components ofinfusion pump assembly 500. Valve assembly 638 may be used inconjunction with shape memory actuator 112 to activate pump plunger106A. Measurement valve 6108, volume sensor valve 612B and/or reservoirvalve 614B may be self-contained valves that are configured to allow forinstallation during assembly of infusion pump assembly 500 by pressingthe valves upward into the lower surface of main body portion 508.

As discussed above, infusion pump assembly 100 may include volume sensorassembly 148 configured to monitor the amount of fluid infused byinfusion pump assembly 100. Further and as discussed above, infusionpump assembly 100 may be configured so that the volume measurementsproduced by volume sensor assembly 148 may be used to control, through afeedback loop, the amount of infusible fluid that is infused into theuser.

The following discussion concerns the design and operation of volumesensor assembly 148 (which is shown in a simplified form in FIG. 19).For the following discussion, the following nomenclature may be used:

Symbols P Pressure p Pressure Perturbation V Volume v VolumePerturbation γ Specific Heat Ratio R Gas Constant ρ Density Z Impedancef Flow friction A Cross sectional Area L Length ω Frequency ζ Dampingratio α Volume Ratio Subscripts 0 Speaker Volume 1 Reference Volume 2Variable Volume k Speaker r Resonant Port z Zero p Pole

Derivation of the Equations for Volume Sensor Assembly 148 Modeling theAcoustic Volumes

The pressure and volume of an ideal adiabatic gas may be related by:

PV^(γ)=K  [EQ #1]

where K is a constant defined by the initial conditions of the system.

EQ #1 may be written in terms of a mean pressure, P, and volume, V, anda small time-dependent perturbation on top of those pressures, p(t),v(t) as follows:

(P+p(t))(V+v(t))^(γ) =K  [EQ #2]

Differentiating this equation may result in:

{dot over (p)}(t)(V+v(t))^(γ)+γ(V+v(t))^(γ−1)(P+p(t)){dot over(v)}(t)=0  [EQ #3]

which may simplify to:

$\begin{matrix}{{{\overset{.}{p}(t)} + {\gamma \frac{P + {p(t)}}{V + {v(t)}}{\overset{.}{v}(t)}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 4} \right\rbrack\end{matrix}$

If the acoustic pressure levels are much less than the ambient pressure,the equation may be further simplified to:

$\begin{matrix}{{{\overset{.}{p}(t)} + {\frac{\gamma \; P}{V}{\overset{.}{v}(t)}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 5} \right\rbrack\end{matrix}$

How good is this assumption? Using the adiabatic relation it may beshown that:

$\begin{matrix}{\frac{P}{V} = {\left( \frac{P + {p(t)}}{V + {v(t)}} \right)\left( \frac{P + {p(t)}}{P} \right)^{- \frac{\gamma + 1}{\gamma}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 6} \right\rbrack\end{matrix}$

Accordingly, the error in the assumption would be:

$\begin{matrix}{{error} = {1 - \left( \frac{P + {p(t)}}{P} \right)^{- \frac{\gamma + 1}{\gamma}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 7} \right\rbrack\end{matrix}$

A very loud acoustic signal (120 dB) may correspond to pressure sinewave with amplitude of roughly 20 Pascal. Assuming air at atmosphericconditions (γ=1.4, P=101325 Pa), the resulting error is 0.03%. Theconversion from dB to Pa is as follows:

$\begin{matrix}{\lambda = {{20\; {\log_{10}\left( \frac{p_{rms}}{p_{ref}} \right)}\mspace{14mu} {or}\mspace{14mu} p_{rms}} = {p_{ref}10^{\frac{\lambda}{20}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 8} \right\rbrack\end{matrix}$

where p_(ref)=20·μPa

Applying the ideal gas law, P=ρRT, and substituting in for pressure mayresult in the following:

$\begin{matrix}{{{\overset{.}{p}(t)} + {\frac{\gamma \; {RT}\; \rho}{V}{\overset{.}{v}(t)}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 9} \right\rbrack\end{matrix}$

EQ #9 may be written in terms of the speed of sound, a=√{square rootover (γRT)} as follows:

$\begin{matrix}{{{\overset{.}{p}(t)} + {\frac{\rho \; a^{2}}{V}{\overset{.}{v}(t)}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 10} \right\rbrack\end{matrix}$

Acoustic impedance for a volume may be defined as follows:

$\begin{matrix}{Z_{v} = {\frac{p(t)}{\overset{.}{v}(t)} = {- \frac{1}{\left( \frac{V}{\rho \; a^{2}} \right)s}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 11} \right\rbrack\end{matrix}$

Modeling the Acoustic Port

The acoustic port may be modeled assuming that all of the fluid in theport essentially moves as a rigid cylinder reciprocating in the axialdirection. All of the fluid in the channel is assumed to travel at thesame velocity, the channel is assumed to be of constant cross section,and the “end effects” resulting from the fluid entering and leaving thechannel are neglected.

If we assume laminar flow friction of the form Δp=fρ{dot over (v)}, thefriction force acting on the mass of fluid in the channel may be writtenas follows:

F={dot over (f)}ρA²{dot over (x)}

A second order differential equation may then be written for thedynamics of the fluid in the channel:

ρLA{umlaut over (x)}=ΔpA−fρA ² {dot over (x)}

or, in terms of volume flow rate:

$\begin{matrix}{\overset{¨}{v} = {{{- \frac{f\; A}{L}}\overset{.}{v}} + {\Delta \; p\frac{A}{\rho \; L}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 14} \right\rbrack\end{matrix}$

The acoustic impedance of the channel may then be written as follows:

$\begin{matrix}{Z_{p} = {\frac{\Delta \; p}{\overset{.}{v}} = {\frac{\rho \; L}{A}\left( {s + \frac{f\; A}{L}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 15} \right\rbrack\end{matrix}$

System Transfer Functions

Using the volume and port dynamics defined above, volume sensor assembly148 may be described by the following system of equations: (k=speaker,r=resonator)

$\begin{matrix}{{{\overset{.}{p}}_{0} - {\frac{\rho \; a^{2}}{V_{0}}{\overset{.}{v}}_{k}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 16} \right\rbrack \\{{{\overset{.}{p}}_{1} + {\frac{\rho \; a^{2}}{V_{1}}\left( {{\overset{.}{v}}_{k} - {\overset{.}{v}}_{r}} \right)}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 17} \right\rbrack \\{{{\overset{.}{p}}_{2} + {\frac{\rho \; a^{2}}{V_{2}}{\overset{.}{v}}_{r}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 18} \right\rbrack \\{{\overset{¨}{v}}_{r} = {{{- \frac{fA}{L}}{\overset{.}{v}}_{r}} + {\frac{A}{\rho \; L}\left( {p_{2} - p_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 19} \right\rbrack\end{matrix}$

One equation may be eliminated if p_(o) is treated as the inputsubstituting in

${\overset{.}{v}}_{k} = {\frac{V_{0}}{\rho \; a^{2}}{{\overset{.}{p}}_{0}.}}$

$\begin{matrix}{{{\overset{.}{p}}_{1} + {\frac{V_{0}}{V_{1}}{\overset{.}{p}}_{0}} - {\frac{\rho \; a^{2}}{V_{1}}{\overset{.}{v}}_{r}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 20} \right\rbrack \\{{{\overset{.}{p}}_{2} + {\frac{\rho \; a^{2}}{V_{2}}{\overset{.}{v}}_{r}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 21} \right\rbrack \\{{\overset{¨}{v}}_{r} = {{{- \frac{fA}{L}}{\overset{.}{v}}_{r}} + {\frac{A}{\rho \; L}p_{2}} - {\frac{A}{\rho \; L}p_{1}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 22} \right\rbrack\end{matrix}$

Cross System Transfer Function

The relationship between the speaker volume and the variable volume maybe referred to as the Cross System transfer function. This transferfunction may be derived from the above equations and is as follows:

$\begin{matrix}{{\frac{p_{2}}{p_{0}} = {\frac{V_{0}}{V_{1}}\frac{\omega_{n}^{2}}{s^{2} + {2{\zeta\omega}_{n}s} + {\alpha\omega}_{n}^{2}}}}{where}} & \left\lbrack {{EQ}\# \mspace{14mu} 23} \right\rbrack \\{{\omega_{n}^{2} = {\frac{a^{2}A}{L}\frac{1}{V_{2}}}},{\zeta = {{\frac{fA}{2L\; \omega_{n}}\mspace{14mu} {and}\mspace{14mu} \alpha} = \left( {1 + \frac{V_{2}}{V_{1}}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 24} \right\rbrack\end{matrix}$

Referring also to FIG. 20, a bode plot of EQ #23 is shown.

The difficulty of this relationship is that the complex poles depend onboth the variable volume, V₂, and the reference volume, V₁. Any changein the mean position of the speaker may result in an error in theestimated volume.

Cross Port Transfer Function

The relationship between the two volumes on each side of the acousticport may be referred to as the Cross Port transfer function. Thisrelationship is as follows:

$\begin{matrix}{\frac{p_{2}}{p_{1}} = \frac{\omega_{n}^{2}}{s^{2} + {2{\zeta\omega}_{n}s} + \omega_{n}^{2}}} & \left\lbrack {{EQ}\# \mspace{14mu} 25} \right\rbrack\end{matrix}$

which is shown graphically in FIG. 21.

This relationship has the advantage that the poles are only dependent onthe variable volume and not on the reference volume. It does, however,have the difficulty that the resonant peak is actually due to theinversion of the zero in the response of the reference volume pressure.Accordingly, the pressure measurement in the reference chamber will havea low amplitude in the vicinity of the resonance, potentially increasingthe noise in the measurement.

Cross Speaker Transfer Function

The pressures may also be measured on each side of the speaker. This isreferred to as the cross speaker transfer function:

$\begin{matrix}{\frac{p_{1}}{p_{0}} = {{- \frac{V_{0}}{V_{1}}}\frac{s^{2} + {2{\zeta\omega}_{n}s} + \omega_{n}^{2}}{s^{2} + {2{\zeta\omega}_{n}s} + {\alpha\omega}_{n}^{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 26} \right\rbrack\end{matrix}$

which is shown graphically in FIG. 22.

This transfer function has a set of complex zeros in addition to the setof complex poles.

Looking at the limits of this transfer function: as

${s->0},{{\frac{p_{1}}{p_{0}}->{- \frac{V_{0}}{V_{1} + V_{2}}}};{{{and}\mspace{14mu} {as}\mspace{14mu} s}->\infty}},{\frac{p_{1}}{p_{0}}->{- {\frac{V_{0}}{V_{1}}.}}}$

Resonance Q Factor and Peak Response

The quality of the resonance is the ratio of the energy stored to thepower loss multiplied by the resonant frequency. For a pure second-ordersystem, the quality factor may be expressed as a function of the dampingratio:

$\begin{matrix}{Q = \frac{1}{2\zeta}} & \left\lbrack {{EQ}\# \mspace{14mu} 27} \right\rbrack\end{matrix}$

The ratio of the peak response to the low-frequency response may also bewritten as a function of the damping ratio:

$\begin{matrix}{{G}_{\omega_{d}} = \frac{1}{\zeta \sqrt{5 - {4\zeta}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 28} \right\rbrack\end{matrix}$

This may occur at the damped natural frequency:

ω_(d)=ω_(n)√{square root over (1−ζ)}  [EQ #29]

Volume Estimation Volume Estimation using Cross-Port Phase

The variable volume (i.e., within volume sensor chamber 620) may also beestimated using the cross-port phase. The transfer function for thepressure ratio across the resonant port may be as follows:

$\begin{matrix}{\frac{p_{2}}{p_{1}} = \frac{\omega_{n}^{2}}{s^{2} + {bs} + \omega_{n}^{2}}} & \left\lbrack {{EQ}\# \mspace{14mu} 30} \right\rbrack\end{matrix}$

At the 90° phase point, ω=ω_(n); where

$\omega_{n}^{2} = {\frac{1}{V_{2}}\frac{a^{2}A}{L}}$

The resonant frequency may be found on the physical system using anumber of methods. A phase-lock loop may be employed to find the 90°phase point—this frequency may correspond to the natural frequency ofthe system. Alternatively, the resonant frequency may be calculatedusing the phase at any two frequencies:

The phase, Φ, at any given frequency will satisfy the followingrelation:

$\begin{matrix}{{{\tan \; \varphi} = \frac{b\; \omega}{\omega^{2} - \omega_{n}^{2}}}{{{where}\mspace{14mu} b} = {\frac{fA}{L}.}}} & \left\lbrack {{EQ}\# \mspace{14mu} 31} \right\rbrack\end{matrix}$

Solving for V₂ results in:

$\begin{matrix}{V_{2} = \frac{\frac{a^{2}A}{L}}{\omega^{2} - {f\; \omega \; \cot \; \varphi}}} & \left\lbrack {{EQ}\# \mspace{14mu} 32} \right\rbrack\end{matrix}$

Accordingly, the ratio of the phases at two different frequencies ω₁ andω₂ can be used to compute the natural frequency of the system:

$\begin{matrix}{{\alpha \; \omega_{n}^{2}} = {\omega_{1}\omega_{2}\frac{\left( {{\omega_{1}\frac{\tan \; \varphi_{1}}{\tan \; \varphi_{2}}} - \omega_{2}} \right)}{\left( {{\omega_{2}\frac{\tan \; \varphi_{1}}{\tan \; \varphi_{2}}} - \omega_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 33} \right\rbrack\end{matrix}$

For computational efficiency, the actual phase does not need to becalculated. All that is needed is the ratio of the real and imaginaryparts of the response (tan Φ).

Re-writing EQ #33 in terms of the variable volume results in:

$\begin{matrix}{\frac{1}{V_{2}} = {\frac{1}{a^{2}}\frac{L}{A}\omega_{1}\omega_{2}\frac{\left( {{\omega_{1}\frac{\tan \; \varphi_{1}}{\tan \; \varphi_{2}}} - \omega_{2}} \right)}{\left( {{\omega_{2}\frac{\tan \; \varphi_{1}}{\tan \; \varphi_{2}}} - \omega_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 34} \right\rbrack\end{matrix}$

Volume Estimation using Swept Sine

The resonant frequency of the system may be estimated using swept-sinesystem identification. In this method, the response of the system to asinusoidal pressure variation may be found at a number of differentfrequencies. This frequency response data may then used to estimate thesystem transfer function using linear regression.

The transfer function for the system may be expressed as a rationalfunction of s. The general case is expressed below for a transferfunction with an n^(th) order numerator and an m^(th) order denominator.N and D are the coefficients for the numerator and denominatorrespectively. The equation has been normalized such that the leadingcoefficient in the denominator is 1.

$\begin{matrix}{{{G(s)} = \frac{{N_{n}s^{n}} + {N_{n - 1}s^{n - 1}} + \ldots + N_{0}}{s^{m} + {D_{m - 1}s^{m - 1}} + {D_{m - 2}s^{m - 2}} + \ldots + D_{0}}}{or}} & \left\lbrack {{EQ}\# \mspace{14mu} 35} \right\rbrack \\{{G(s)} = \frac{\sum\limits_{k = 0}^{n}{N_{k}s^{k}}}{s^{m} + {\sum\limits_{k = 0}^{m - 1}{D_{k}s^{k}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 36} \right\rbrack\end{matrix}$

This equation may be re-written as follows:

$\begin{matrix}{{Gs}^{m} = {{\sum\limits_{k = 0}^{n}{N_{k}s^{k}}} - {G{\sum\limits_{k = 0}^{m - 1}{D_{k}s^{k}}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 37} \right\rbrack\end{matrix}$

Representing this summation in matrix notation resulting in thefollowing:

$\begin{matrix}{\begin{bmatrix}{G_{1}s_{1}^{m}} \\\vdots \\{G_{k}s_{k}^{m}}\end{bmatrix} = {\begin{bmatrix}s_{1}^{n} & \ldots & s_{1}^{0} & {{- G_{1}}s_{1}^{m - 1}} & \ldots & {{- G_{1}}s_{1}^{0}} \\\vdots & \; & \vdots & \vdots & \; & \vdots \\s_{k}^{n} & \ldots & s_{k}^{0} & {{- G_{k}}s_{k}^{m - 1}} & \ldots & {{- G_{k}}s_{k}^{0}}\end{bmatrix}\begin{bmatrix}N_{n} \\\vdots \\N_{0} \\D_{m - 1} \\\vdots \\D_{0}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 38} \right\rbrack\end{matrix}$

where k is the number of data points collected in the swept sine. Tosimplify the notation, this equation may be summarized using thevectors:

y=Xc  [EQ #39]

where y is k by 1, x is k by (m+n−1) and c is (m+n−1) by 1. Thecoefficients may then be found using a least square approach. The errorfunction may be written as follows:

e=y−Xc  [EQ #40]

The function to be minimized is the weighted square of the errorfunction; W is a k×k diagonal matrix.

e ^(T) We=(y−Xc)^(T) W(y−Xc)  [EQ #41]

e ^(T) We=y ^(T) Wy−(y ^(T) WXc)^(T) −y ^(T) WXc+c ^(T) x ^(T) WXc  [EQ#42]

As the center two terms are scalars, the transpose may be neglected.

$\begin{matrix}{{e^{T}{We}} = {{y^{T}{Wy}} - {2y^{T}{WXc}} + {c^{T}x^{T}{WXc}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 43} \right\rbrack \\{\frac{{\partial e^{T}}{We}}{\partial c} = {{{{- 2}X^{T}{Wy}} + {2X^{T}{WXc}}} = 0}} & \left\lbrack E \right. \\{c = {\left( {X^{T}{WX}} \right)^{- 1}X^{T}{Wy}}} & \left\lbrack {{EQ}\# \mspace{14mu} 45} \right\rbrack\end{matrix}$

It may be necessary to use the complex transpose in all of these cases.This approach may result in complex coefficients, but the process may bemodified to ensure that all the coefficients are real. The least-squareminimization may be modified to give only real coefficients if the errorfunction is changed to be

e ^(T) We=Re(y−Xc)^(T) WRe(y−Xc)+Im(y−Xc)^(T) WIm(y−Xc)  [EQ #46]

Accordingly, the coefficients may be found with the relation:

c=(Re(X)^(T) WRe(X)+Im(X)^(T) WIm(X))⁻¹(Re(X)^(T) WRe(y)+Im(X)^(T)WIm(y))  [EQ #47]

Solution for a 2nd Order System

For a system with a 0^(th) order numerator and a second orderdenominator as shown in the transfer function:

$\begin{matrix}{{G(s)} = \frac{N_{0}}{s^{2} + {D_{1}s} + D_{0}}} & \left\lbrack {{EQ}\# \mspace{14mu} 48} \right\rbrack\end{matrix}$

The coefficients in this transfer function may be found based on theexpression found in the previous section:

$\begin{matrix}{{{c = {\left( {{{{Re}(X)}^{T}{{W{Re}}(X)}} + {{{Im}(X)}^{T}{{W{Im}}(X)}}} \right)^{- 1}\left( {{{{Re}(X)}^{T}{{W{Re}}(y)}} + {{{Im}(X)}^{T}{{W{Im}}(y)}}} \right)}}\mspace{79mu} {{where}\text{:}}}\mspace{56mu}} & \left\lbrack {{EQ}\# \mspace{14mu} 49} \right\rbrack \\{\mspace{79mu} {{y = \begin{bmatrix}{G_{1}s_{1}^{2}} \\\vdots \\{G_{k}s_{k}^{2}}\end{bmatrix}},{X = \begin{bmatrix}1 & {{- G_{1}}s_{1}} & {- G_{1}} \\\vdots & \vdots & \vdots \\1 & {{- G_{k}}s_{k}} & {- G_{k}}\end{bmatrix}},{{{and}\mspace{14mu} c} = \begin{bmatrix}N_{0} \\D_{1} \\D_{0}\end{bmatrix}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 50} \right\rbrack\end{matrix}$

To simplify the algorithm, we may combine some of terms:

c=D⁻¹b  [EQ #51]

where:

D=Re(X)^(T) WRe(X)+Im(X)^(T) WIm(X)  [EQ #52]

b=Re(X)^(T) WRe(y)−Im(X)^(T) WIm(y)  [EQ #53]

To find an expression for D in terms of the complex response vector Gand the natural frequency s=jω, X may be split into its real andimaginary parts:

$\begin{matrix}{{{{Re}(X)} = \begin{bmatrix}1 & {\omega_{k}{{Im}\left( G_{1} \right)}} & {- {{Re}\left( G_{1} \right)}} \\\vdots & \vdots & \vdots \\1 & {\omega_{k}{{Im}\left( G_{k} \right)}} & {- {{Re}\left( G_{k} \right)}}\end{bmatrix}},{{{Im}(X)} = \begin{bmatrix}0 & {{- \omega_{k}}{{Re}\left( G_{1} \right)}} & {- {{Im}\left( G_{1} \right)}} \\\vdots & \vdots & \vdots \\0 & {{- \omega_{k}}{{Re}\left( G_{k} \right)}} & {- {{Im}\left( G_{k} \right)}}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 54} \right\rbrack\end{matrix}$

The real and imaginary portions of the expression for D above may thenbecome:

$\begin{matrix}{{{{Re}(X)}^{T}{{W{Re}}(X)}} = {\quad\begin{bmatrix}{\sum\limits_{i = 1}^{k}w_{i}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}}}} \\{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}^{2}\omega_{i}^{2}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}{{Re}\left( G_{i} \right)}\omega_{i}}}} \\{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}{{Re}\left( G_{i} \right)}\omega_{i}}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}^{2}}}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 55} \right\rbrack \\{{{{Im}(X)}^{T}{{W{Im}}(X)}} = \begin{bmatrix}0 & 0 & 0 \\0 & {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}^{2}\omega_{i}^{2}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}{{Re}\left( G_{i} \right)}\omega_{i}}} \\0 & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}{{Re}\left( G_{i} \right)}\omega_{i}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}^{2}}}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 56} \right\rbrack\end{matrix}$

Combining these terms results in the final expression for the D matrix,which may contain only real values.

$\begin{matrix}{D = \begin{bmatrix}{\sum\limits_{i = 1}^{k}w_{i}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}}}} \\{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}}} & \begin{matrix}{{\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}^{2}}} +} \\{{Im}\left( G_{i} \right)^{2}\omega_{i}^{2}}\end{matrix} & 0 \\{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}}}} & 0 & \begin{matrix}{{\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}^{2}}} +} \\{{Im}\left( G_{i} \right)}^{2}\end{matrix}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 57} \right\rbrack\end{matrix}$

The same approach may be taken to find an expression for the b vector interms of G and ω. The real and imaginary parts of y are as follows:

$\begin{matrix}{{{{Re}(y)} = \begin{bmatrix}{{- {{Re}\left( G_{1} \right)}}\omega_{1}^{2}} \\\vdots \\{{- {{Re}\left( G_{k} \right)}}\omega_{k}^{2}}\end{bmatrix}},{{{Im}(y)} = \begin{bmatrix}{{- {{Im}\left( G_{1} \right)}}\omega_{1}^{2}} \\\vdots \\{{- {{Im}\left( G_{k} \right)}}\omega_{k}^{2}}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 58} \right\rbrack\end{matrix}$

Combining the real and imaginary parts results in the expression for theb vector as follows:

$\begin{matrix}\begin{matrix}{b = {{{{Re}(X)}^{T}{{W{Re}}(y)}} + {{{Im}(X)}^{T}{{W{Im}}(y)}}}} \\{= {\quad\begin{bmatrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{2}}}} \\0 \\{\sum\limits_{i = 1}^{k}{{w_{i}\left( {{{Re}\left( G_{i} \right)}^{2} + {{Im}\left( G_{i} \right)}^{2}} \right)}\omega_{i}^{2}}}\end{bmatrix}}}\end{matrix} & \left\lbrack {{EQ}\# \mspace{14mu} 59} \right\rbrack\end{matrix}$

The next step is to invert the D matrix. The matrix is symmetric andpositive-definite so the number of computations needed to find theinverse will be reduced from the general 3×3 case. The generalexpression for a matrix inverse is:

$\begin{matrix}{D^{- 1} = {\frac{1}{\det (D)}{{adj}(D)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 60} \right\rbrack\end{matrix}$

If D is expressed as follows:

$\begin{matrix}{D = \begin{bmatrix}d_{11} & d_{12} & d_{13} \\d_{12} & d_{22} & 0 \\d_{13} & 0 & d_{33}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 61} \right\rbrack\end{matrix}$

then the adjugate matrix may be written as follows:

$\begin{matrix}\begin{matrix}{{{adj}(D)} = \begin{bmatrix}{\begin{matrix}d_{22} & 0 \\0 & d_{33}\end{matrix}} & {- {\begin{matrix}d_{12} & 0 \\d_{13} & d_{33}\end{matrix}}} & {\begin{matrix}d_{12} & d_{22} \\d_{13} & 0\end{matrix}} \\{- {\begin{matrix}d_{12} & d_{13} \\0 & d_{33}\end{matrix}}} & {\begin{matrix}d_{11} & d_{13} \\d_{13} & d_{33}\end{matrix}} & {- {\begin{matrix}d_{11} & d_{12} \\d_{13} & 0\end{matrix}}} \\{\begin{matrix}d_{12} & d_{13} \\d_{22} & 0\end{matrix}} & {- {\begin{matrix}d_{11} & d_{13} \\d_{12} & 0\end{matrix}}} & {\begin{matrix}d_{11} & d_{12} \\d_{12} & d_{22}\end{matrix}}\end{bmatrix}} \\{= \begin{bmatrix}a_{11} & a_{12} & a_{13} \\a_{12} & a_{22} & a_{23} \\a_{13} & a_{32} & a_{33}\end{bmatrix}}\end{matrix} & \left\lbrack {{EQ}\# \mspace{14mu} 62} \right\rbrack\end{matrix}$

Due to symmetry, only the upper diagonal matrix may need to becalculated.

The Determinant may then be computed in terms of the adjugate matrixvalues, taking advantage of the zero elements in the original array:

det(D)=a ₁₂ d ₁₂ +a ₂₂ d ₂₂  [EQ #63]

Finally, the inverse of D may be written as follows:

$\begin{matrix}{D^{- 1} = {\frac{1}{\det (D)}{{adj}(D)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 64} \right\rbrack\end{matrix}$

Since we are trying to solve:

$\begin{matrix}{{c = {{D^{- 1}b} = {\frac{1}{\det (D)}{{adj}(D)}b}}}{{then}\text{:}}} & \left\lbrack {{EQ}\# \mspace{14mu} 65} \right\rbrack \\{c = {{{\frac{1}{\det (D)}\begin{bmatrix}a_{11} & a_{12} & a_{13} \\a_{12} & a_{22} & a_{23} \\a_{13} & a_{32} & a_{33}\end{bmatrix}}\begin{bmatrix}b_{1} \\0 \\b_{3}\end{bmatrix}}\mspace{14mu} = {\frac{1}{\det (D)}\begin{bmatrix}{{a_{11}b_{1}} + {a_{13}b_{3}}} \\{{a_{12}b_{1}} + {a_{23}b_{3}}} \\{{a_{13}b_{1}} + {a_{33}b_{3}}}\end{bmatrix}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 66} \right\rbrack\end{matrix}$

The final step is to get a quantitative assessment of how well the datafits the model. Accordingly, the original expression for the error is asfollows:

e ^(T) We=Re(y−Xc)^(T) WRe(y−Xc)+Im(y−Xc)^(T) WIm(y−Xc)  [EQ #67]

This may be expressed in terms of the D matrix and the b and c vectorsas follows:

e ^(T) We=h−2c ^(T) b+c ^(T) Dc  [EQ #68]

where:

$\begin{matrix}{h = {{{{Re}\left( y^{T} \right)}{{W{Re}}(y)}} + {{{Im}\left( y^{T} \right)}{{W{Im}}(y)}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 69} \right\rbrack \\{h = {\sum\limits_{i = 1}^{k}{{w_{i}\left( {{{Re}\left( G_{i} \right)}^{2} + {{Im}\left( G_{i} \right)}^{2}} \right)}\omega_{i}^{4}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 70} \right\rbrack\end{matrix}$

The model fit error may also be used to detect sensor failures.

Alternate Solution for a 2nd Order System

$\begin{matrix}{{{G(s)} = \frac{{N_{n}s^{n}} + {N_{n - 1}s^{n - 1}} + \ldots + N_{0}}{s^{m} + {D_{m - 1}s^{m - 1}} + {D_{m - 2}s^{m - 2}} + \ldots + D_{0}}}{or}} & \left\lbrack {{EQ}\# \mspace{14mu} 71} \right\rbrack \\{{G(s)} = \frac{\sum\limits_{k = 0}^{n}{N_{k}s^{k}}}{s^{m} + {\sum\limits_{k = 0}^{m - 1}{D_{k}s^{k}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 72} \right\rbrack\end{matrix}$

This equation may be re-written as follows:

$\begin{matrix}{G = {{\sum\limits_{k = 0}^{n}{N_{k}s^{k - m}}} - {G{\sum\limits_{k = 0}^{m - 1}{D_{k}s^{k - m}}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 73} \right\rbrack\end{matrix}$

Putting this summation into matrix notation results in the following:

$\begin{matrix}{\begin{bmatrix}G_{1} \\\vdots \\G_{k}\end{bmatrix} = {\begin{bmatrix}s_{1}^{n - m} & \ldots & s_{1}^{- m} & {{- G_{1}}s_{1}^{- 1}} & \ldots & {{- G_{1}}s_{1}^{- m}} \\\vdots & \; & \vdots & \vdots & \; & \vdots \\s_{k}^{n - m} & \ldots & s_{k}^{- m} & {{- G_{k}}s_{k}^{- 1}} & \ldots & {{- G_{k}}s_{k}^{- m}}\end{bmatrix}\begin{bmatrix}N_{n} \\\vdots \\N_{0} \\D_{m - 1} \\\vdots \\D_{0}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 74} \right\rbrack\end{matrix}$

For a system with a 0^(th) order numerator and a second orderdenominator as shown in the transfer function:

$\begin{matrix}{{G(s)} = \frac{N_{0}}{s^{2} + {D_{1}s} + D_{0}}} & \left\lbrack {{EQ}\# \mspace{14mu} 75} \right\rbrack\end{matrix}$

The coefficients in this transfer function may be found based on theexpression found in the previous section:

$\begin{matrix}{{c = {\left( {{{{Re}(X)}^{T}W\; {{Re}(X)}} + {{{Im}(X)}^{T}{{W{Im}}(X)}}} \right)^{- 1}\left( {{{{Re}(X)}^{T}{{W{Re}}(y)}} + {{{Im}(X)}^{T}{{W{Im}}(y)}}} \right)}}{where}} & \left\lbrack {{EQ}\# \mspace{14mu} 76} \right\rbrack \\{{y = \begin{bmatrix}G_{1} \\\vdots \\G_{k}\end{bmatrix}},\mspace{14mu} {X = \begin{bmatrix}s_{1}^{- 2} & {{- G_{1}}s_{1}^{- 1}} & {{- G_{1}}s_{1}^{- 2}} \\\vdots & \vdots & \vdots \\s_{k}^{- 2} & {{- G_{k}}s_{k}^{- 1}} & {{- G_{k}}s_{k}^{- 2}}\end{bmatrix}},\mspace{14mu} {{{and}\mspace{14mu} c} = \begin{bmatrix}N_{0} \\D_{1} \\D_{0}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 77} \right\rbrack\end{matrix}$

To simplify the algorithm, some terms may be combined:

c=D⁻¹b  [EQ ·78]

where:

D=Re(X)^(T) WRe(X)+Im(X)^(T) WIm(X)  [EQ #79]

b=Re(X)^(T) WRe(y)+Im(X)^(T) WIM(y)  [EQ #80]

To find an expression for D in terms of the complex response vector Gand the natural frequency s=jω, split X may be split into its real andimaginary parts:

$\begin{matrix}{{{Re}(X)} = \begin{bmatrix}{- \omega_{1}^{- 2}} & {{- \omega_{1}^{- 1}}{{Im}\left( G_{1} \right)}} & {\omega_{1}^{- 2}{{Re}\left( G_{1} \right)}} \\\vdots & \vdots & \vdots \\{- \omega_{k}^{- 2}} & {{- \omega_{k}^{- 1}}{{Im}\left( G_{k} \right)}} & {\omega_{k}^{- 2}{{Re}\left( G_{k} \right)}}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 81} \right\rbrack \\{{{Im}(X)} = \begin{bmatrix}0 & {{- \omega_{1}^{- 1}}{{Re}\left( G_{1} \right)}} & {\omega_{1}^{- 2}{{Im}\left( G_{1} \right)}} \\\vdots & \vdots & \vdots \\0 & {{- \omega_{k}^{- 1}}{{Re}\left( G_{k} \right)}} & {\omega_{k}^{- 2}{{Im}\left( G_{k} \right)}}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 82} \right\rbrack\end{matrix}$

The real and imaginary portions of the expression for D above may thenbecome:

$\begin{matrix}{{{{Re}(X)}^{T}W\; {{Re}( X)}} = \left\lbrack \begin{matrix}{\sum\limits_{i = 1}^{k}{w_{i}\omega_{i}^{- 4}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}^{- 3}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{- 4}}}} \\{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}^{- 3}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}^{2}\omega_{i}^{- 2}}} & \begin{matrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} \\{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{- 4}}}} & \begin{matrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} & \begin{matrix}{\sum\limits_{i = 1}^{k}{w_{i}{Re}}} \\{\left( G_{i} \right)^{2}\omega_{i}^{- 4}}\end{matrix}\end{matrix} \right\rbrack} & \left\lbrack {{EQ}\# \mspace{14mu} 83} \right\rbrack \\{{{{Im}(X)}^{T}{{W{Im}}(X)}} = \begin{bmatrix}0 & 0 & 0 \\0 & {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}^{2}\omega_{i}^{- 2}}} & \begin{matrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} \\0 & \begin{matrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}^{2}\omega_{i}^{- 4}}}\end{bmatrix}} & \left\lbrack {{EQ}\# \mspace{14mu} 84} \right\rbrack\end{matrix}$

Combining these terms results in the final expression for the D matrix,which may contain only real values.

$\begin{matrix}{D = \left\lbrack \begin{matrix}{\sum\limits_{i = 1}^{k}{w_{i}\omega_{i}^{- 4}}} & {\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}^{- 3}}} & {- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{- 4}}}} \\{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}\omega_{i}^{- 3}}} & {\sum\limits_{i = 1}^{k}{{w_{i}\begin{pmatrix}{{{Re}\left( G_{i} \right)}^{2} +} \\{{Im}\left( G_{i} \right)}^{2}\end{pmatrix}}\omega_{i}^{- 2}}} & \begin{matrix}{{- 2}{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} \\{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{- 4}}}} & \begin{matrix}{{- 2}{\sum\limits_{i = 1}^{k}{w_{i}{{Im}\left( G_{i} \right)}}}} \\{{{Re}\left( G_{i} \right)}\omega_{i}^{- 3}}\end{matrix} & {\sum\limits_{i = 1}^{k}{{w_{i}\begin{pmatrix}{{{Re}\left( G_{i} \right)^{2}} +} \\{{Im}\left( G_{i} \right)}^{2}\end{pmatrix}}\omega_{i}^{- 4}}}\end{matrix} \right\rbrack} & \left\lbrack {{EQ}\# \mspace{11mu} 85} \right\rbrack\end{matrix}$

The same approach may be taken to find an expression for the b vector interms of G and ω. The real and imaginary parts of y areas follows:

$\begin{matrix}{{{{Re}(y)} = \begin{bmatrix}{- {{Re}\left( G_{1} \right)}} \\\vdots \\{- {{Re}\left( G_{k} \right)}}\end{bmatrix}},\mspace{14mu} {{{Im}(y)} = \begin{bmatrix}{- {{Im}\left( G_{1} \right)}} \\\vdots \\{- {{Im}\left( G_{k} \right)}}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 86} \right\rbrack\end{matrix}$

Combining the real and imaginary parts results in the expression for theb vector as follows:

$\begin{matrix}{b = {{{{{Re}(X)}^{T}{{W{Re}}(y)}} + {{{Im}(X)}^{T}{{W{Im}}(y)}}}\mspace{14mu} = \begin{bmatrix}{- {\sum\limits_{i = 1}^{k}{w_{i}{{Re}\left( G_{i} \right)}\omega_{i}^{- 2}}}} \\{- {\sum\limits_{i = 1}^{k}{w_{i}\left( {{{Im}\left( G_{i} \right)} + {{{Re}\left( G_{i} \right)}\omega_{i}^{- 1}}} \right.}}} \\{\sum\limits_{i = 1}^{k}{{w_{i}\left( {{{Re}\left( G_{i} \right)}^{2} + {{Im}\left( G_{i} \right)}^{2}} \right)}\omega_{i}^{- 2}}}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 87} \right\rbrack\end{matrix}$

Implementing Acoustic Volume Sensing Collecting the Frequency ResponseData and Computing the Complex Response

To implement volume sensor assembly 148, volume sensor assembly 148should determine the relative response of reference microphone 626 andinvariable volume microphone 630 to the acoustic wave set up by speakerassembly 622. This may be accomplished by driving speaker assembly 622with a sinusoidal output at a known frequency; the complex response ofmicrophones 626, 630 may then be found at that driving frequency.Finally, the relative response of microphones 626, 630 may be found andcorrected for alternating sampling by e.g., an analog-to-digitalconverter (i.e., ADC).

Additionally, the total signal variance may be computed and compared tothe variance of pure tone extracted using the discrete Fourier transform(i.e., DFT). This may result in a measure of how much of the signalpower comes from noise sources or distortion. This value may then beused to reject and repeat bad measurements.

Computing the Discrete Fourier Transform

The signal from the microphone may be sampled synchronously with theoutput to speaker assembly 622 such that a fixed number of points, N,are taken per wavelength. The measured signal at each point in thewavelength may be summed over an integer number of wavelengths, M, andstored in an array x by the ISR for processing after all the data forthat frequency has been collected.

A DFT may be performed on the data at the integer value corresponding tothe driven frequency of the speaker. The general expression for thefirst harmonic of a DFT is as follows:

$\begin{matrix}{x_{k} = {\frac{2}{MN}{\sum\limits_{n = 0}^{N - 1}{x_{n}^{{- \frac{2\pi \; }{N}}{kn}}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 88} \right\rbrack\end{matrix}$

The product MN may be the total number of points and the factor of twomay be added such that the resulting real and imaginary portions of theanswer match the amplitude of the sine wave:

$\begin{matrix}{x_{n} = {{{{re}\left( x_{k} \right)}{\cos \left( {\frac{2\pi}{N}{kn}} \right)}} + {{{im}\left( x_{k} \right)}{\sin \left( {\frac{2\pi}{N}{kn}} \right)}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 89} \right\rbrack\end{matrix}$

This real part of this expression may be as follows:

$\begin{matrix}{{{re}(x)} = {\frac{2}{MN}{\sum\limits_{n = 0}^{N - 1}{x_{n}{\cos \left( {\frac{2\pi}{N}n} \right)}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 90} \right\rbrack\end{matrix}$

We may take advantage of the symmetry of the cosine function to reducethe number of computations needed to compute the DFT. The expressionabove may be equivalent to:

$\begin{matrix}{{{re}(x)} = {\frac{2}{MN}\begin{bmatrix}{\left( {x_{0} - x_{\frac{1}{2}N}} \right) + {\sum\limits_{n = 1}^{{\frac{1}{4}N} - 1}{\sin \left( {\frac{\pi}{2} - {\frac{2\pi}{N}n}} \right)}}} \\\begin{bmatrix}{\left( {x_{n} - x_{\frac{1}{2}N\; 4n}} \right) -} \\\left( {x_{{\frac{1}{2}N} + n} - x_{N - n}} \right)\end{bmatrix}\end{bmatrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 91} \right\rbrack\end{matrix}$

Similarly, for the imaginary portion of the equation:

$\begin{matrix}{{{im}(x)} = {{- \frac{2}{MN}}{\sum\limits_{n = 0}^{N - 1}{x_{n}{\sin \left( {\frac{2\pi}{N}n} \right)}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 92} \right\rbrack\end{matrix}$

which may be expressed as follows:

$\begin{matrix}{{{im}(x)} = {- {\frac{2}{MN}\begin{bmatrix}{\left( {x_{\frac{1}{4}N} - x_{\frac{1}{4}N}} \right) + {\sum\limits_{n = 1}^{{\frac{1}{4}N} - 1}{\sin \left( {\frac{2\pi}{N}n} \right)}}} \\\begin{bmatrix}{\left( {x_{n} - x_{{\frac{1}{2}N} + n}} \right) +} \\\left( {x_{{\frac{1}{2}N} + n} - x_{N - n}} \right)\end{bmatrix}\end{bmatrix}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 93} \right\rbrack\end{matrix}$

The variance of this signal may be calculated as follows:

$\begin{matrix}{\sigma^{2} = {\frac{1}{2}\left( {{{re}(x)}^{2} + {{im}(x)}^{2}} \right)}} & \left\lbrack {{EQ}\# \mspace{14mu} 94} \right\rbrack\end{matrix}$

The maximum possible value of the real and imaginary portions of x maybe 2¹¹; which corresponds to half the AD range. The maximum value of thetone variance may be 2²¹; half the square of the AD range.

Computing the Signal Variance

The pseudo-variance of the signal may be calculated using the followingrelation:

$\begin{matrix}{\sigma^{2} = {{\frac{1}{{NM}^{2}}{\sum\limits_{n = 0}^{N - 1}x_{n}^{2}}} - {\frac{1}{N^{2}M^{2}}\left( {\sum\limits_{n = 0}^{N - 1}x_{n}} \right)^{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 95} \right\rbrack\end{matrix}$

The result may be in the units of AD counts squared. It may only be the“pseudo-variance” because the signal has been averaged over M periodsbefore the variance is calculated over the N samples in the “averaged”period. This may be a useful metric, however, for finding if the“averaged” signal looks like a sinusoid at the expected frequency. Thismay be done by comparing the total signal variance to that of thesinusoid found in the discrete Fourier transform.

The summation may be on the order of

${\sum\limits_{n = 0}^{N - 1}x_{n}^{2}} = {O\left( {{NM}^{2}2^{24}} \right)}$

for a 12-bit ADC. If N<2⁷=128 and M<2⁶=64, then the summation will beless than 2⁴³ and may be stored in a 64-bit integer. The maximumpossible value of the variance may result if the ADC oscillated betweena value of 0 and 2¹² on each consecutive sample. This may result in apeak variance of

${\frac{1}{4}\left( 2^{12} \right)^{2}} = 2^{22}$

so the result may be stored at a maximum of a 1/2⁹ resolution in asigned 32-bit integer.

Computing the Relative Microphone Response

The relative response (G) of microphones 626, 630 may be computed fromthe complex response of the individual microphones:

$\begin{matrix}{G = {\frac{x_{var}}{x_{ref}} = {\frac{x_{var}}{x_{ref}}\frac{x_{ref}^{*}}{x_{ref}^{*}}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 96} \right\rbrack \\{{{Re}(G)} = \frac{{{{Re}\left( x_{var} \right)}{{Re}\left( x_{ref} \right)}} + {{{Im}\left( x_{var} \right)}{{Im}\left( x_{ref} \right)}}}{{{Re}\left( x_{ref} \right)}^{2} + {{Im}\left( x_{ref} \right)}^{2}}} & \left\lbrack {{EQ}\# \mspace{14mu} 97} \right\rbrack \\{{{Im}(G)} = \frac{{{{Re}\left( x_{ref} \right)}{{Im}\left( x_{var} \right)}} - {{{Re}\left( x_{var} \right)}{{Im}\left( x_{ref} \right)}}}{{{Re}\left( x_{ref} \right)}^{2} + {{Im}\left( x_{ref} \right)}^{2}}} & \left\lbrack {{EQ}\# \mspace{14mu} 98} \right\rbrack\end{matrix}$

The denominator of either expression may be expressed in terms of thereference tone variance computed in the previous section as follows:

Re(x _(ref))+Im(x _(ref))²=2σ_(ref) ²  [EQ #99]

Correcting for A/D Skew

The signals from microphones 626, 630 may not be sampled simultaneously;the A/D ISR alternates between microphones 626, 630, taking a total of Nsamples per wavelength for each of microphones 626, 630. The result maybe a phase offset between two microphones 626, 630 of π/N. To correctfor this phase offset, a complex rotation may be applied to the relativefrequency response computed in the previous section:

$\begin{matrix}{G_{rotated} = {G \cdot \left( {{\cos \left( \frac{\pi}{N} \right)} + {\; {\sin \left( \frac{\pi}{N} \right)}}} \right)}} & \left\lbrack {{EQ}\# \mspace{14mu} 100} \right\rbrack\end{matrix}$

Reference Models Second and Higher Order Models

Leakage through the seals (e.g., seal assembly 1404) of volume sensorchamber 620 may be modeled as a second resonant port (e.g., port 1504,FIG. 23) connected to an external volume (e.g., external volume 1506,FIG. 23).

The system of equations describing the three-chamber configuration maybe as follows:

$\begin{matrix}{{{\overset{.}{p}}_{1} + {\frac{\rho \; a^{2}}{V_{1}}\left( {{\overset{.}{v}}_{k} - {\overset{.}{v}}_{r\; 12}} \right)}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 101} \right\rbrack \\{{{\overset{.}{p}}_{2} + {\frac{\rho \; a^{2}}{V_{2}}\left( {{\overset{.}{v}}_{r\; 12} - {\overset{.}{v}}_{r\; 23}} \right)}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 102} \right\rbrack \\{{\overset{¨}{v}}_{r\; 12} = {{{- \frac{f_{12}A_{12}}{L_{12}}}{\overset{.}{v}}_{r\; 12}} + {\frac{A_{12}}{\rho \; L_{12}}\left( {p_{2} - p_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 103} \right\rbrack \\{{{\overset{.}{p}}_{3} + {\frac{\rho \; a^{2}}{V_{3}}{\overset{.}{v}}_{r\; 23}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 104} \right\rbrack \\{{\overset{¨}{v}}_{r\; 23} = {{{- \frac{f_{23}A_{23}}{L_{23}}}{\overset{.}{v}}_{r\; 23}} + {\frac{A_{23}}{\rho \; L_{23}}\left( {p_{3} - p_{2}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 105} \right\rbrack\end{matrix}$

Putting these equations into state-space results in the following:

$\begin{matrix}{\left\lbrack \begin{matrix}{\overset{.}{p}}_{1} \\{\overset{.}{p}}_{2} \\{\overset{.}{p}}_{3} \\{\overset{¨}{v}}_{12} \\{\overset{¨}{v}}_{23}\end{matrix} \right\rbrack = {{\left\lbrack \begin{matrix}0 & 0 & 0 & \frac{\rho \; a^{2}}{V_{1}} & 0 \\0 & 0 & 0 & {- \frac{\rho \; a^{2}}{V_{2}}} & \frac{\rho \; a^{2}}{V_{2}} \\0 & 0 & 0 & 0 & {- \frac{\rho \; a^{2}}{V_{3}}} \\{- \frac{A_{12}}{\rho \; L_{12}}} & \frac{A_{12}}{\rho \; L_{12}} & 0 & {- b_{12}} & 0 \\0 & {- \frac{A_{23}}{\rho \; L_{23}}} & \frac{A_{23}}{\rho \; L_{23}} & 0 & {- b_{23}}\end{matrix} \right\rbrack\left\lbrack \begin{matrix}p_{1} \\p_{2} \\p_{3} \\v_{12} \\v_{23}\end{matrix} \right\rbrack} + {\left\lbrack \begin{matrix}{- \frac{\rho \; a^{2}}{V_{1}}} \\0 \\0 \\0 \\0\end{matrix} \right\rbrack \left\lbrack {\overset{.}{v}}_{k} \right\rbrack}}} & \left\lbrack {{EQ}\# \mspace{14mu} 106} \right\rbrack\end{matrix}$

the frequency response of which may be represented graphically in theBode diagram shown in FIG. 24 and which may also be written in transferfunction form:

$\begin{matrix}{\frac{p_{2}}{p_{1}} = \frac{\omega_{12}^{2}\left( {s^{2} + {b_{23}s} + \omega_{23}^{2}} \right)}{\begin{matrix}{{\left( {s^{2} + {b_{12}s} + \omega_{12}^{2}} \right)\left( {s^{2} + {b_{23}s} + \omega_{23}^{2}} \right)} +} \\{\frac{V_{3}}{V_{2}}{\omega_{23}^{2}\left( {s + b_{12}} \right)}s}\end{matrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 107} \right\rbrack\end{matrix}$

Expanding the denominator results in the following:

$\begin{matrix}{\frac{p_{2}}{p_{1}} = \frac{\omega_{12}^{2}\left( {s^{2} + {b_{23}s} + \omega_{23}^{2}} \right)}{\begin{matrix}{s^{4} + {\left( {b_{12} + b_{23}} \right)s^{3}} +} \\{{\left( {{b_{12}b_{23}} + \omega_{12}^{2} + {\omega_{23}^{2}\left( {1 + \frac{V_{3}}{V_{2}}} \right)}} \right)s^{2}} +} \\{{\left( {{b_{23}\omega_{12}^{2}} + {b_{12}{\omega_{23}^{2}\left( {1 + \frac{V_{3}}{V_{2}}} \right)}}} \right)s} + {\omega_{12}^{2}\omega_{23}^{2}}}\end{matrix}}} & \left\lbrack {{EQ}\# \mspace{14mu} 108} \right\rbrack\end{matrix}$

A bubble underneath the diaphragm material in the variable volume willfollow the same dynamic equations as a leakage path. In this case, thediaphragm material may act as the resonant mass rather than the leakageport. Accordingly, the equation may be as follows:

m{umlaut over (x)}=ΔpA−b _(m) {dot over (x)}  [EQ #109]

wherein m is the mass of the diaphragm, A is the cross sectional area ofthe diaphragm that can resonate, and b_(m), is the mechanical damping.EQ #106 may be written in terms of the volume flow rate:

$\begin{matrix}{\overset{¨}{v} = {{{- \frac{b}{m}}\overset{.}{v}} + {\Delta \; p\frac{A^{2}}{m}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 110} \right\rbrack\end{matrix}$

wherein the volume of the air bubble is V₃. If the bubble volume issubstantially smaller than the acoustic volume V₃<<V₂ than the transferfunction may be simplified to:

$\begin{matrix}{\frac{p_{2}}{p_{1}} = \frac{\omega_{12}^{2}\left( {s^{2} + {b_{23}s} + \omega_{23}^{2}} \right)}{\left( {s^{2} + {b_{12}s} + \omega_{12}^{2}} \right)\left( {s^{2} + {b_{23}s} + {\omega_{23}^{2}\left( {1 + \frac{V_{3}}{V_{2}}} \right)}} \right)}} & \left\lbrack {{EQ}\# \mspace{14mu} 111} \right\rbrack\end{matrix}$

Second Order with Time Delay

The volume sensor assembly 148 equations derived above assume that thepressure is the same everywhere in the acoustic volume. This is only anapproximation, as there are time delays associated with the propagationof the sound waves through the volume. This situation may look like atime delay or a time advance based on the relative position of themicrophone and speakers.

A time delay may be expressed in the Laplace domain as:

G(s)=e ^(−ΔTs)  [EQ #112]

which makes for a non-linear set of equations. However, a first-orderPade approximation of the time delay may be used as follows:

$\begin{matrix}{{G(s)} = {- \frac{s + \frac{2}{\Delta \; T}}{s - \frac{2}{\Delta \; T}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 113} \right\rbrack\end{matrix}$

which is shown graphically in FIG. 25.

Three Chamber Volume Estimation

Volume sensor assembly 148 may also be configured using a thirdreference volume (e.g., reference volume 1508; FIG. 26) connected with aseparate resonant port (e.g., port 1510; FIG. 26). This configurationmay allow for temperature-independent volume estimation.

The system of equations describing the three-chamber configuration areas follows:

$\begin{matrix}{{{\overset{.}{p}}_{1} + {\frac{\rho \; a^{2}}{V_{1}}\left( {{\overset{.}{v}}_{k} - {\overset{.}{v}}_{r\; 12} - {\overset{.}{v}}_{r\; 13}} \right)}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 114} \right\rbrack \\{{{\overset{.}{p}}_{2} + {\frac{\rho \; a^{2}}{V_{2}}{\overset{.}{v}}_{r\; 12}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 115} \right\rbrack \\{{\overset{¨}{v}}_{r\; 12} = {{{- \frac{f_{12}A_{12}}{L_{12}}}{\overset{.}{v}}_{r\; 12}} + {\frac{A_{12}}{\rho \; L_{12}}\left( {p_{2} - p_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 116} \right\rbrack \\{{{\overset{.}{p}}_{3} + {\frac{\rho \; a^{2}}{V_{3}}{\overset{.}{v}}_{r\; 13}}} = 0} & \left\lbrack {{EQ}\# \mspace{14mu} 117} \right\rbrack \\{{\overset{¨}{v}}_{r\; 13} = {{{- \frac{f_{13}A_{13}}{L_{13}}}{\overset{.}{v}}_{r\; 13}} + {\frac{A_{13}}{\rho \; L_{13}}\left( {p_{2} - p_{1}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 118} \right\rbrack\end{matrix}$

Using these equations and solving for the transfer function across eachof the resonant ports results in the following:

$\begin{matrix}{{\frac{p_{2}}{p_{1}} = \frac{\omega_{n\; 12}^{2}}{s^{2} + {2\zeta_{12}\omega_{n\; 12}s} + \omega_{n\; 12}^{2}}}{where}} & \left\lbrack {{EQ}\# \mspace{14mu} 119} \right\rbrack \\{\omega_{n\; 12} = {{\frac{1}{V_{2}}\frac{a^{2}A_{12}}{L_{12}}\mspace{14mu} {and}\mspace{14mu} \zeta} = \frac{f_{12}A_{12}}{2L_{12}\omega_{n\; 12}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 120} \right\rbrack \\{{\frac{p_{3}}{p_{1}} = \frac{\omega_{n\; 13}^{2}}{s^{2} + {2\zeta_{13}\omega_{n\; 13}s} + \omega_{n\; 13}^{2}}}{where}} & \left\lbrack {{EQ}\# \mspace{14mu} 121} \right\rbrack \\{\omega_{n\; 13} = {{\frac{1}{V_{3}}\frac{a^{2}A_{13}}{L_{13}}\mspace{14mu} {and}\mspace{14mu} \zeta} = \frac{f_{13}A_{13}}{2L_{13}\omega_{n\; 13}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 122} \right\rbrack\end{matrix}$

The volume of volume sensor chamber 620 may be estimated using the ratioof the natural frequency of the two resonant ports as follows:

$\begin{matrix}{\frac{\omega_{n\; 13}^{2}}{\omega_{n\; 12}^{2}} = {\frac{V_{2}}{V_{3}}\frac{A_{13}}{A_{12}}\frac{L_{12}}{L_{13}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 123} \right\rbrack\end{matrix}$

EQ #120 illustrates that the volume of volume sensor chamber 620 may beproportional to reference volume 1508. The ratio of these two volumes(in the ideal model) may only depend on the geometry of the resonantport (e.g., port 1510; FIG. 26) and has no dependence upon temperature.

Exponential Volume Model

Assume the flow out through the flow resistance has the following form:

$\begin{matrix}{{\overset{.}{V}}_{out} = \frac{V_{avs}}{\tau}} & \left\lbrack {{EQ}\# \mspace{14mu} 124} \right\rbrack\end{matrix}$

Assuming a fixed input flow rate from the pump chamber, the volume ofvolume sensor chamber 620 is based upon the following differentialequation:

$\begin{matrix}{{\overset{.}{V}}_{avs} = {{{\overset{.}{V}}_{in} - {\overset{.}{V}}_{out}} = {{\overset{.}{V}}_{in} - \frac{{\overset{.}{V}}_{avs}}{\tau}}}} & \left\lbrack {{EQ}{\# 125}} \right\rbrack\end{matrix}$

which gives the following solution assuming a zero initial volume:

$\begin{matrix}{V_{avs} = {{\overset{.}{V}}_{in}{\tau\left( {1 - ^{- \frac{t}{\tau}}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 126} \right\rbrack\end{matrix}$

Accordingly, the output flow rate flows:

$\; \begin{matrix}{{\overset{.}{V}}_{out} = {{\overset{.}{V}}_{in}\left( {1 - ^{- \frac{t}{\tau}}} \right)}} & \left\lbrack {{EQ}\# \mspace{14mu} 127} \right\rbrack\end{matrix}$

The volume delivered during the pump phase may be written:

$\begin{matrix}{V_{out} = {{\overset{.}{V}}_{in}\left\lbrack {t - {\tau\left( {1 - ^{- \frac{t}{\tau}}} \right)}} \right\rbrack}} & \left\lbrack {{EQ}\# \mspace{14mu} 128} \right\rbrack\end{matrix}$

Device Calibration

The model fit allows the resonant frequency of the port to be extractedfrom the sine sweep data. The next step is to relate this value to thedelivered volume. The ideal relationship between the resonant frequencyand the delivered volume to be expressed as follows:

$\begin{matrix}{\omega_{n}^{2} = {\frac{a^{2}A}{L}\frac{1}{V_{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 129} \right\rbrack\end{matrix}$

The speed of sound will vary with temperature, so it may be useful tosplit out the temperature effects.

$\begin{matrix}{\omega_{n}^{2} = {\frac{\gamma \; {RA}}{L}\frac{T}{V_{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 130} \right\rbrack\end{matrix}$

The volume may then be expressed as a function of the measured resonantfrequency and the temperature:

$\begin{matrix}{V_{2} = {C\frac{T}{\omega_{n}^{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 131} \right\rbrack\end{matrix}$

Where c is the calibration constant

$C = \frac{\gamma \; {RA}}{L}$

Implementation Details End Effects

The air resonating in the port (e.g., port assembly 624) may extend outinto the acoustic volumes at the end of each oscillation. The distancethe air extends may be estimated based on the fundamental volume sensorassembly equations. For any given acoustic volume, the distance the airextends into the volume may be expressed as a function of the pressureand port cross-sectional area:

$\begin{matrix}{x = {\frac{V}{\rho \; a^{2}A}p}} & \left\lbrack {{EQ}\# \mspace{14mu} 132} \right\rbrack\end{matrix}$

If we assume the following values:

$\begin{matrix}{V = {28.8 \times 10^{- 6}L}} & \left\lbrack {{EQ}\# \mspace{14mu} 133} \right\rbrack \\{\rho = {1.292\frac{kg}{m^{3}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 134} \right\rbrack \\{a = {340\frac{m}{s}}} & \left\lbrack {{EQ}\# \mspace{14mu} 135} \right\rbrack \\{d = {0.5 \cdot {mm}}} & \left\lbrack {{EQ}\# \mspace{14mu} 136} \right\rbrack \\{p = {{1 \cdot {Pa}}\mspace{14mu} \left( {{Approximately}\mspace{14mu} 100\mspace{14mu} {dB}} \right)}} & \left\lbrack {{EQ}\# \mspace{14mu} 137} \right\rbrack\end{matrix}$

Accordingly, the air will extend roughly 1.9 mm in to the acousticchamber.

Sizing V1 (i.e., the fixed volume) relative to V2 (i.e., the variablevolume)

Sizing V₁ (e.g., fixed volume 1500) may require trading off acousticvolume with the relative position of the poles and zeros in the transferfunction. The transfer function for both V₁ and V₂ (e.g., variablevolume 1502) are shown below relative to the volume displacement ofspeaker assembly 622.

$\begin{matrix}{\frac{p_{2}}{v_{k}} = {{- \frac{\rho \; a^{2}}{V_{1}}}\frac{\omega_{n}^{2}}{s^{2} + {2{\zeta\omega}_{n}s} + {\alpha\omega}_{n}^{2}}}} & \left\lbrack {{EQ}\# \mspace{14mu} 138} \right\rbrack \\{{\frac{p_{1}}{v_{k}} = {{- \frac{\rho \; a^{2}}{V_{1}}}\frac{s^{2} + {2{\zeta\omega}_{n}s} + {\alpha\omega}_{n}^{2}}{s^{2} + {2{\zeta\omega}_{n}s} + {\alpha\omega}_{n}^{2}}}}{where}} & \left\lbrack {{EQ}\# \mspace{14mu} 139} \right\rbrack \\{{\omega_{n}^{2} = {\frac{a^{2}A}{L}\frac{1}{V_{2}}}},\mspace{14mu} {\zeta = {{\frac{f\; A}{2L\; \omega_{n}}\mspace{14mu} {and}\mspace{14mu} \alpha} = \left( {1 + \frac{V_{2}}{V_{1}}} \right)}}} & \left\lbrack {{EQ}\# \mspace{14mu} 140} \right\rbrack\end{matrix}$

As V₁ is increased the gain may decrease and the speaker may be drivenat a higher amplitude to get the same sound pressure level. However,increasing V₁ may also have the benefit of moving the complex zeros inthem transfer function toward the complex poles. In the limiting casewhere V₁→∞, α→1 and you have pole-zero cancellation and a flat response.Increasing V₁, therefore, may have the benefit of reducing both theresonance and the notch in the p₁ transfer function, and moving the p₂,poles toward ω_(n); resulting in a lower sensitivity to measurementerror when calculating the p₂/p₁ transfer function.

FIG. 27 is a graphical representation of:

$\begin{matrix}\frac{P_{1}}{v_{k}} & \left\lbrack {{EQ}{\# 141}} \right\rbrack\end{matrix}$

FIG. 28 is a graphical representation of

$\begin{matrix}\frac{P_{2}}{v_{k}} & \left\lbrack {{EQ}{\# 142}} \right\rbrack\end{matrix}$

Aliasing

Higher frequencies may alias down to the frequency of interest, whereinthe aliased frequency may be expressed as follows:

f=|f _(n) −nf _(s)|  [EQ #143]

where f_(s) is the sampling frequency, f_(n) is the frequency of thenoise source, n is a positive integer, and f is the aliased frequency ofthe noise source.

The demodulation routine may effectively filter out noise except at thespecific frequency of the demodulation. If the sample frequency is setdynamically to be a fixed multiple of the demodulation frequency, thenthe frequency of the noise that can alias down to the demodulationfrequency may be a fixed set of harmonics of that fundamental frequency.

For example, if the sampling frequency is eight times the demodulationfrequency, then the noise frequencies that can alias down to thatfrequency are as follows:

$\begin{matrix}{\begin{matrix}{\frac{f_{n}}{f} = \left\{ {\frac{1}{{n\; \beta} + 1},\frac{1}{{n\; \beta} - 1}} \right\}} \\{= \left\{ {\frac{1}{7},\frac{1}{9},\frac{1}{15},\frac{1}{17},\frac{1}{23},\frac{1}{25},\ldots}\mspace{14mu} \right\}}\end{matrix}{{{where}\mspace{14mu} \beta} = {\frac{f_{s}}{f} = 8.}}\mspace{11mu} {{{{For}\mspace{14mu} \beta} = 16},{{the}\mspace{14mu} {following}\mspace{14mu} {series}\mspace{14mu} {would}\mspace{14mu} {result}\text{:}}}} & \left\lbrack {{EQ}{\# 144}} \right\rbrack \\{\frac{f_{n}}{f} = \left\{ {\frac{1}{15},\frac{1}{17},\frac{1}{31},\frac{1}{33},\ldots}\mspace{14mu} \right\}} & \left\lbrack {{EQ}{\# 145}} \right\rbrack\end{matrix}$

Performance Sensitivity to Temperature

The sensitivity to temperature may be split into a gain change and anoise change. If the temperature is off by a factor of dT, the resultinggain error may be:

$\begin{matrix}{V_{2} = {c\left( {\frac{T_{2}}{\omega_{2}^{2}} - \frac{T_{1}}{\omega_{1}^{2}}} \right)}} & \left\lbrack {{EQ}{\# 147}} \right\rbrack\end{matrix}$

Accordingly, if the same temperature is used for both sine sweeps, anyerror in the temperature measurement may look like a gain change to thesystem.

$\begin{matrix}{e_{gain} = {1 - \frac{T_{measured}}{T_{actual}}}} & \left\lbrack {{EQ}{\# 148}} \right\rbrack\end{matrix}$

Therefore, for a 1° K temperature error, the resulting volume error maybe 0.3% at 298° K. This error may include both the error in thetemperature sensor and the difference between the sensor temperature andthe temperature of the air within volume sensor assembly 148.

The measurement, however, may be more susceptible to noise in thetemperature measurement. A temperature change during the differentialsine sweeps may result in an error that looks more like an offset ratherthan a gain change:

$\begin{matrix}{V_{error} = {\frac{c}{\omega^{2}}\Delta \; T}} & \left\lbrack {{EQ}{\# 149}} \right\rbrack\end{matrix}$

Accordingly, if the measurement varies by 0.1 K during the twomeasurement sine sweeps, the difference may be 0.012 uL. Therefore, itmay be better to use a consistent temperature estimate for each deliveryrather than taking a separate temperature measurement for each sinesweep (as shown in FIG. 30).

The LM73 temperature sensor has a published accuracy of +/−C and aresolution of 0.03 C. Further, the LM73 temperature sensor seems toconsistently have a startup transient of about 0.3° C. that takes aboutfive sine sweeps to level out (as shown in FIG. 31).

Since the above-described infusion pump assemblies (e.g., infusion pumpassembly 100, 100′, 400, 500) provides discrete deliveries of infusiblefluid, the above-described infusion pump assemblies may be modeledentirely in the discrete domain (in the manner shown in FIG. 32), whichmay be reduced to the following:

$\begin{matrix}{{G_{p}(z)} = \frac{Kz}{z - 1}} & \left\lbrack {{EQ}{\# 150}} \right\rbrack\end{matrix}$

A discrete-time P1 regulator may perform according to the following:

$\begin{matrix}{{G_{c}(z)} = {K_{p}\left( {1 + {\frac{T_{s}}{T_{l}}\frac{z}{z - 1}}} \right)}} & \left\lbrack {{EQ}{\# 151}} \right\rbrack\end{matrix}$

The AVS system described above works by comparing the acoustic responsein fixed volume 1500 and variable volume 1502 to a speaker driven inputand extracting the volume of the variable volume 1502. As such, there isa microphone in contact with each of these separate volumes (e.g.,microphones 626, 630). The response of variable volume microphone 630may also be used in a more gross manner to detect the presence orabsence of disposable housing assembly 114. Specifically, if disposablehousing assembly 114 is not attached to (i.e., positioned proximate)variable volume 1502, essentially no acoustic response to the speakerdriven input should be sensed. The response of fixed volume 1500,however, should remain tied to the speaker input. Thus, the microphonedata may be used to determine whether disposable housing assembly 114 bysimply ensuring that both microphones exhibit an acoustic response.

In the event that microphone 626 (i.e., the microphone positionedproximate fixed volume 1500) exhibits an acoustic response andmicrophone 630 (i.e., the microphone positioned proximate variablevolume 1502) does not exhibit an acoustic response, it may be reasonablyconcluded that disposable housing assembly 114 is not attached toreusable housing assembly 102. It should be noted that a failure ofvariable volume microphone 630 may also appear to be indicative ofdisposable housing assembly 114 not being attached, as the failure ofvariable volume microphone 630 may result in a mid-range reading that isnearly indistinguishable from the microphone response expected whendisposable housing assembly 114 is not attached.

For the following discussion, the following nomenclature may be used:

Symbols α_(max)(f) maximum read at a given frequency α_(min)(f) minimumread at a given frequency δ difference between max and min sums findividual frequency F set of sine sweep frequencies N number offrequencies in each sine sweep, F φ boolean disposable attached flagσmax sum of maximum ADC reads σmin sum of minimum ADC reads T max/minADC difference threshold Subscripts i sweep number ref reference volumevar variable volume

As part of the demodulation routine employed in each frequency responsecalculation, the minimum and maximum readings of both fixed volumemicrophone 626 and variable volume microphone 630 may be calculated. Thesum of these maximum and minimum values may be calculated over theentire sine-sweep (as discussed above) for both microphone 626 andmicrophone 630 as follows.

$\begin{matrix}{{\sigma max} = {\sum\limits^{f \in F}\; {\alpha_{\max}(f)}}} & \left\lbrack {{EQ}{\# 152}} \right\rbrack \\{{\sigma min} = {\sum\limits^{f \in F}\; {\alpha_{\min}(f)}}} & \left\lbrack {{EQ}{\# 153}} \right\rbrack\end{matrix}$

and the difference between these two summations may be simplified asfollows:

δ=σmax−σmin

While δ may be divided by the number of sine sweeps to get the averageminimum/maximum difference for the sine sweep (which is then compared toa threshold), the threshold may equivalently be multiplied by N forcomputational efficiency. Accordingly, the basic disposable detectionalgorithm may be defined as follows:

$\begin{matrix}{\varphi_{2} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} \delta_{var}} > {N*T}} \\0 & {{{{{{if}\mspace{14mu} \delta_{var}} < {N*T}}\&}\mspace{14mu} \delta_{ref}} > {N*T}}\end{matrix} \right.} & \left\lbrack {{EQ}{\# 155}} \right\rbrack\end{matrix}$

The additional condition that the maximum/minimum difference be greaterthan the threshold is a check performed to ensure that a failed speakeris not the cause of the acoustic response received. This algorithm maybe repeated for any sine-sweep, thus allowing a detachment of disposablehousing assembly 114 to be sensed within e.g., at most two consecutivesweeps (i.e., in the worst case scenario in which disposable housingassembly 114 is removed during the second half of an in-progress sinesweep).

Thresholding for the above-described algorithm may be based entirely onnumerical evidence. For example, examination of typical minimum/maximumresponse differences may show that no individual difference is ever lessthan five hundred ADC counts. Accordingly, all data examined whiledisposable housing assembly 114 is detached from reusable housingassembly 102 may show that all minimum/maximum response differences asbeing well under five hundred ADC counts. Thus, the threshold for δ maybe set at T=500.

While volume sensor assembly 148 is described above as being utilizedwithin an infusion pump assembly (e.g., infusion pump assembly 100),this is for illustrative purposes only and is not intended to be alimitation of this disclosure, as other configurations are possible andare considered to be within the scope of this disclosure. For example,volume sensor assembly 148 may be used within a process controlenvironment for e.g., controlling the quantity of chemicals mixedtogether. Alternatively, volume sensor assembly 148 may be used within abeverage dispensing system to control e.g., the quantity of ingredientsmixed together.

While volume sensor assembly 148 is described above as utilizing a port(e.g., port assembly 624) as a resonator, this is for illustrativepurposes only, as other configurations are possible and are consideredto be within the scope of this disclosure. For example, a solid mass(not shown) may be suspended within port assembly 624 and may functionas a resonator for volume sensor assembly 148. Specifically, the mass(not shown) for the resonator may be suspended on a diaphragm (notshown) spanning port assembly 624. Alternatively, the diaphragm itself(not shown) may act as the mass for the resonator. The natural frequencyof volume sensor assembly 148 may be a function of the volume ofvariable volume 1502. Accordingly, if the natural frequency of volumesensor assembly 148 can be measured, the volume of variable volume 1502may be calculated.

The natural frequency of volume sensor assembly 148 may be measured in anumber of different ways. For example, a time-varying force may beapplied to the diaphragm (not shown) and the relationship between thatforce and the motion of the diaphragm (not shown) may be used toestimate the natural frequency of volume sensor assembly 148.Alternately the mass (not shown) may be perturbed and then allowed tooscillate. The unforced motion of the mass (not shown) may then be usedto calculate the natural frequency of volume sensor assembly 148.

The force applied to the resonant mass (not shown) may be accomplishedin various ways, examples of which may include but are not limited to:

-   -   speaker assembly 622 may create a time-varying pressure within        fixed volume 1500;    -   the resonant mass (not shown) may be a piezoelectric material        responding to a time-varying voltage/current; and    -   the resonant mass (not shown) may be a voice coil responding to        a time-varying voltage/current

The force applied to the resonant mass may be measured in various ways,examples of which may include but are not limited to:

-   -   measuring the pressure in the fixed volume;    -   the resonant mass (not shown) may be a piezoelectric material;        and    -   a strain gauge may be connected to the diaphragm (not shown) or        other structural member supporting the resonant mass (not        shown).

Similarly, the displacement of the resonant mass (not shown) may beestimated by measuring the pressure in the variable volume, or measureddirectly in various ways, examples of which may include but are notlimited to:

-   -   via piezoelectric sensor;    -   via capacitive sensor;    -   via optical sensor;    -   via Hall-effect sensor;    -   via a potentiometer (time varying impedance) sensor;    -   via an inductive type sensor; and    -   via a linear variable differential transformer (LVDT)

Further, the resonant mass (not shown) may be integral to either theforce or displacement type sensor (i.e. the resonant mass (not shown)may be made of piezoelectric material).

The application of force and measurement of displacement may beaccomplished by a single device. For example, a piezoelectric materialmay be used for the resonant mass (not shown) and a time-varyingvoltage/current may be applied to the piezoelectric material to create atime-varying force. The resulting voltage/current applied to thepiezoelectric material may be measured and the transfer function betweenthe two used to estimate the natural frequency of volume sensor assembly148.

As discussed above, the resonant frequency of volume sensor assembly 148may be estimated using swept-sine system identification. Specifically,the above-described model fit may allow the resonant frequency of theport assembly to be extracted from the sine sweep data, which may thenbe used to determine the delivered volume. The ideal relationshipbetween the resonant frequency and the delivered volume may be expressedas follows:

$\begin{matrix}{\omega_{n}^{2} = {\frac{a^{2}A}{L}\frac{1}{V_{2}}}} & \left\lbrack {{EQ}{\# 126}} \right\rbrack\end{matrix}$

The speed of sound will vary with temperature, so it may be useful tosplit out the temperature effects.

$\begin{matrix}{\omega_{n}^{2} = {\frac{\gamma \; {RA}}{L}\frac{T}{V_{2}}}} & \left\lbrack {{EQ}{\# 126}} \right\rbrack\end{matrix}$

The volume may then be expressed as a function of the measured resonantfrequency and the temperature:

$\begin{matrix}{V_{2} = {C\frac{T}{\omega_{n}^{2}}}} & \left\lbrack {{EQ}{\# 127}} \right\rbrack\end{matrix}$

Where c is the calibration constant

$C = {\frac{\gamma \; {RA}}{L}.}$

Infusion pump assembly 100 may then compare this calculated volume V₂(i.e., representative of the actual volume of infusible fluid deliveredto the user) to the target volume (i.e., representative of the quantityof fluid that was supposed to be delivered to the user). For example,assume that infusion pump assembly 100 was to deliver a 0.100 unit basaldose of infusible fluid to the user every thirty minutes. Further,assume that upon effectuating such a delivery, volume sensor assembly148 indicates a calculated volume V₂ (i.e., representative of the actualvolume of infusible fluid delivered to the user) of 0.095 units ofinfusible fluid.

When calculating volume V₂, infusion pump assembly 100 may firstdetermine the volume of fluid within volume sensor chamber 620 prior tothe administration of the dose of infusible fluid and may subsequentlydetermine the volume of fluid within volume sensor chamber 620 after theadministration of the dose of infusible fluid, wherein the difference ofthose two measurements is indicative of V₂ (i.e., the actual volume ofinfusible fluid delivered to the user). Accordingly, V₂ is adifferential measurement.

V2 may be the total air space over the diaphragm in the variable volumechamber. The actual fluid delivery to the patient may be the differencein V2 from when the chamber was full to after the measurement valve wasopened and the chamber was emptied. V2 may not directly be the deliveredvolume. For example, the air volume may be measured and a series ofdifferential measurements may be taken. For occlusion, an emptymeasurement may be taken, the chamber may be filed, a full measurementmay be taken, and then a final measurement may be taken after the exitvalve is open. Accordingly, the difference between the first and secondmeasurement may be the amount pumped and the difference between thesecond and third is the amount delivered to the patient.

Accordingly, electrical control assembly 110 may determine that theinfusible fluid delivered is 0.005 units under what was called for. Inresponse to this determination, electrical control assembly 110 mayprovide the appropriate signal to mechanical control assembly 104 sothat any additional necessary dosage may be pumped. Alternatively,electrical control assembly 110 may provide the appropriate signal tomechanical control assembly 104 so that the additional dosage may bedispensed with the next dosage. Accordingly, during administration ofthe next 0.100 unit dose of the infusible fluid, the output command forthe pump may be modified based on the difference between the target andamount delivered.

Referring also to FIG. 33, there is shown one particular implementationof a control system for controlling the quantity of infusible fluidcurrently being infused based, at least in part, on the quantity ofinfusible fluid previously administered. Specifically and continuingwith the above-stated example, assume for illustrative purposes thatelectrical control assembly 110 calls for the delivery of a 0.100 unitdose of the infusible fluid to the user. Accordingly, electrical controlassembly 110 may provide a target differential volume signal 1600 (whichidentifies a partial basal dose of 0.010 units of infusible fluid percycle of shape memory actuator 112) to volume controller 1602.Accordingly and in this particular example, shape memory actuator 112may need to be cycled ten times in order to achieve the desired basaldose of 0.100 units of infusible fluid (i.e., 10 cycles×0.010 units percycle=0.100 units). Volume controller 1602 in turn may provide “on-time”signal 1606 to SMA (i.e., shape memory actuator) controller 1608. Alsoprovided to SMA controller 1608 is battery voltage signal 1610.

Specifically, shape-memory actuator 112 may be controlled by varying theamount of thermal energy (e.g., joules) applied to shape-memory actuator112. Accordingly, if the voltage level of battery 606 is reduced, thequantity of joules applied to shape-memory actuator 112 may also bereduced for a defined period of time. Conversely, if the voltage levelof battery 606 is increased, the quantity of joules applied to shapememory actuator 112 may also be increased for a defined period of time.Therefore, by monitoring the voltage level of battery 606 (via batteryvoltage signal 1610), the type of signal applied to shape-memoryactuator 112 may be varied to ensure that the appropriate quantity ofthermal energy is applied to shape-memory actuator 112 regardless of thebattery voltage level.

SMA controller 1608 may process “on-time” signal 1606 and batteryvoltage signal 1610 to determine the appropriate SMA drive signal 1612to apply to shape-memory actuator 112. One example of SMA drive signal1612 may be a series of binary pulses in which the amplitude of SMAdrive signal 1612 essentially controls the stroke length of shape-memoryactuator 112 (and therefore pump assembly 106) and the duty cycle of SMAdrive signal 1612 essentially controls the stroke rate of shape-memoryactuator 112 (and therefore pump assembly 106). Further, since SMA drivesignal 1612 is indicative of a differential volume (i.e., the volumeinfused during each cycle of shape memory actuator 112), SMA drivesignal 1612 may be integrated by discrete time integrator 1614 togenerate volume signal 1616 which may be indicative of the totalquantity of infusible fluid infused during a plurality of cycles ofshape memory actuator 112. For example, since (as discussed above) itmay take ten cycles of shape memory actuator 112 (at 0.010 units percycle) to infuse 0.100 units of infusible fluid, discrete timeintegrator 1614 may integrate SMA drive signal 1612 over these tencycles to determine the total quantity infused of infusible fluid (asrepresented by volume signal 1616).

SMA drive signal 1612 may actuate pump assembly 106 for e.g. one cycle,resulting in the filling of volume sensor chamber 620 included withinvolume sensor assembly 148. Infusion pump assembly 100 may then make afirst measurement of the quantity of fluid included within volume sensorchamber 620 (as discussed above). Further and as discussed above,measurement valve assembly 610 may be subsequently energized, resultingin all or a portion of the fluid within volume sensor chamber 620 beingdelivered to the user. Infusion pump assembly 100 may then make ameasurement of the quantity of fluid included within volume sensorchamber 620 (as described above) and use those two measurements todetermine V₂ (i.e., the actual volume of infusible fluid delivered tothe user during the current cycle of shape memory actuator 112). Oncedetermined, V₂ (i.e., as represented by signal 1618) may be provided(i.e., fed back) to volume controller 1602 for comparison to theearlier-received target differential volume.

Continuing with the above-stated example in which the differentialtarget volume was 0.010 units of infusible fluid, assume that V₂ (i.e.,as represented by signal 1618) identifies 0.009 units of infusible fluidas having been delivered to the user. Accordingly, infusion pumpassembly 100 may increase the next differential target volume to 0.011units to offset the earlier 0.001 unit shortage. Accordingly and asdiscussed above, the amplitude and/or duty cycle of SMA drive signal1612 may be increased when delivering the next basal dose of theinfusible fluid to the user. This process may be repeated for theremaining nine cycles of shape memory actuator 112 (as discussed above)and discrete time integrator 1614 may continue to integrate SMA drivesignal 1612 (to generate volume signal 1616) which may define the totalquantity of infusible fluid delivered to the user.

Referring also to FIG. 34, there is shown one possible embodiment ofvolume controller 1602. In this particular implementation, volumecontroller 1602 may include PI (proportional-integrator) controller1650. Volume controller 1602 may include feed forward controller 1652for setting an initial “guess” concerning “on-time” signal 1606. Forexample, for the situation described above in which target differentialvolume signal 1600 identifies a partial basal dose of 0.010 units ofinfusible fluid per cycle of shape memory actuator 112, feed forwardcontroller 1652 may define an initial “on-time” of e.g., onemillisecond. Feed forward controller 1652 may include e.g., a lookuptable that define an initial “on-time” that is based, at least in part,upon target differential volume signal 1600. Volume controller 1602 mayfurther include discrete time integrator 1654 for integrating targetdifferential volume signal 1600 and discrete time integrator 1656 forintegrating V₂ (i.e., as represented by signal 1618).

Referring also to FIG. 35, there is shown one possible embodiment offeed forward controller 1652. In this particular implementation, feedforward controller 1652 may define a constant value signal 1658 and mayinclude amplifier 1660 (e.g., a unity gain amplifier), the output ofwhich may be summed with constant value signal 1658 at summing node1662. The resulting summed signal (i.e., signal 1664) may be provided toas an input signal to e.g., lookup table 1666, which may be processed togenerate the output signal of feed forward controller 1652.

As discussed above, pump assembly 106 may be controlled by shape memoryactuator 112. Further and as discussed above, SMA controller 1608 mayprocess “on-time” signal 1606 and battery voltage signal 1610 todetermine the appropriate SMA drive signal 1612 to apply to shape-memoryactuator 112.

Referring also to FIGS. 36-37, there is shown one particularimplementation of SMA controller 1608. As discussed above, SMAcontroller 1608 may be responsive to “on-time” signal 1606 and batteryvoltage signal 1610 and may provide SMA drive signal 1612 toshape-memory actuator 112. SMA controller 1608 may include a feedbackloop (including unit delay 1700), the output of which may be multipliedwith battery voltage signal 1610 at multiplier 1702. The output ofmultiplier 1702 may be amplified with e.g., unity gain amplifier 1704.The output of amplifier 1704 may be applied to the negative input ofsumming node 1706 (to which “on-time” signal 1606 is applied). Theoutput of summing node 1706 may be amplified (via e.g., unity gainamplifier 1708). SMA controller may also include feed forward controller1710 to provide an initial value for SMA drive signal 1612 (in a fashionsimilar to feed forward controller 1652 of volume controller 1602; SeeFIG. 35). The output of feed forward controller 1710 may be summed atsumming node 1712 with the output of amplifier 1708 and an integratedrepresentation (i.e., signal 1714) of the output of amplifier 1708 toform SMA drive signal 1612.

SMA drive signal 1612 may be provided to control circuitry thateffectuates the application of power to shape-memory actuator 112. Forexample, SMA drive signal 1612 may be applied to switching assembly 1716that may selectively apply current signal 1718 (supplied from battery606) and/or fixed signal 1720 to shape-memory actuator. For example, SMAdrive signal 1612 may effectuate the application of energy (suppliedfrom battery 606 via current signal 1718) via switching assembly 1716 ina manner that achieves the duty cycle defined by SMA drive signal 1612.Unit delay 1722 may generate a delayed version of the signal applied toshape-memory actuator 112 to form battery voltage signal 1610 (which maybe applied to SMA controller 1608).

When applying power to shape-memory actuator 112, voltage may be appliedfor a fixed amount of time and: a) at a fixed duty cycle with anunregulated voltage; b) at a fixed duty cycle with a regulated voltage;c) at a variable duty cycle based upon a measured current value; d) at avariable duty cycle based upon a measured voltage value; and e) at avariable duty cycle based upon the square of a measured voltage value.Alternatively, voltage may be applied to shape-memory actuator 112 for avariable amount of time based upon a measured impedance.

When applying an unregulated voltage for a fixed amount of time at afixed duty cycle, inner loop feedback may not be used and shape memoryactuator may be driven at a fixed duty cycle and with an on-timedetermined by the outer volume loop.

When applying a regulated voltage for a fixed amount of time at a fixedduty cycle, inner loop feedback may not be used and shape memoryactuator 112 may be driven at a fixed duty cycle and with an on-timedetermined by the outer volume loop.

When applying an unregulated voltage at a variable duty cycle based upona measured current value, the actual current applied to shape-memoryactuator 112 may be measured and the duty cycle may be adjusted duringthe actuation of shape-memory actuator 112 to maintain the correct meancurrent.

When applying an unregulated voltage at a variable duty cycle based upona measured voltage value, the actual voltage applied to shape-memoryactuator 112 may be measured and the duty cycle may be adjusted duringthe actuation of shape-memory actuator 112 to maintain the correct meanvoltage.

When applying an unregulated voltage at a variable duty cycle based uponthe square of a measured voltage value, the actual voltage applied toshape-memory actuator 112 may be measured and the duty cycle may beadjusted during the actuation of shape-memory actuator 112 to maintainthe square of the voltage at a level required to provide the desiredlevel of power to shape-memory actuator 112 (based upon the impedance ofshape-memory actuator 112).

Referring also to FIG. 38A-38B, there is shown other implementations ofSMA controller 1608. Specifically, FIG. 38A is an electrical schematicthat includes a microprocessor and various control loops that may beconfigured to provide a PWM signal that may open and close the switchassembly. The switch assembly may control the current that is allowed toflow through the shape memory actuator. The battery may provide thecurrent to the shape memory actuator. Further, 114B discloses a volumecontroller and an inner shape memory actuator controller. The shapememory actuator controller may provide a PWM signal to the pump, whichmay be modified based on the battery voltage. This may occur for a fixedontime, the result being a volume that may be measured by volume sensorassembly 148 and fed back into the volume controller.

In our preferred embodiment, we vary the duty cycle based on themeasured battery voltage to give you approximately consistent power. Weadjust the duty cycle to compensate for a lower battery voltage. Batteryvoltage may change for two reasons: 1) as batteries are discharged, thevoltage slowly decreases; and 2) when you apply a load to a battery ithas an internal impedance so its voltage dips. This is something thathappens in any type of system, and we compensate for that by adjustingthe duty cycle, thus mitigating the lower or varying battery voltage.Battery voltage may be measured by the microprocessor. In othersystems: 1) voltage may be regulated (put a regulator to maintain thevoltage at a steady voltage); 2) feedback based on something else (i.e.,speed or position of a motor, not necessarily measuring the batteryvoltage).

Other configurations may be utilized to control the shape memoryactuator. For example: A) the shape memory actuator may be controlled atfixed duty cycle with unregulated voltage. As voltage varies, therepeatablity of heating the shape memory actuator is reduced. B) a fixedduty cycle, regulated voltage may be utilized which compensate forchanges in battery voltage. However, regulate the voltage down is lessefficient due to energy of energy. C) the duty cycle may be varied basedon changes in current (which may required more complicated measurementcircuitry. D) The duty cycle may be varied based on measured voltage. E)The duty cycle may be varied based upon the square of the current. orthe square of the voltage divided by resistance. F) the voltage may beapplied for a variable amount of time based on the measured impedance(e.g., may measure impedance using Wheatstone gauge (not shown)). Theimpedance of the shape memory actuator may be correlated to strain(i.e., may, correlate how much the SMA moves based on its impedance).

Referring also to FIG. 39 and as discussed above, to enhance the safetyof infusion pump assembly 100, electrical control assembly 110 mayinclude two separate and distinct microprocessors, namely supervisorprocessor 1800 and command processor 1802. Specifically, commandprocessor 1802 may perform the functions discussed above (e.g.,generating SMA drive signal 1612) and may control relay/switchassemblies 1804, 1806 that control the functionality of (in thisexample) shape memory actuators 112, 632 (respectively). Commandprocessor 1802 may receive feedback from signal conditioner 1808concerning the condition (e.g., voltage level) of the voltage signalapplied to shape memory actuators 112, 632. Command processor 1800 maycontrol relay/switch assembly 1810 independently of relay/switchassemblies 1804, 1806. Accordingly, when an infusion event is desired,both of supervisor processor 1800 and command processor 1802 must agreethat the infusion event is proper and must both actuate their respectiverelays/switches. In the event that either of supervisor processor 1800and command processor 1802 fails to actuate their respectiverelays/switches, the infusion event will not occur. Accordingly throughthe use of supervisor processor 1800 and command processor 1802 and thecooperation and concurrence that must occur, the safety of infusion pumpassembly 100 is enhanced. \

The supervisor processor may prevent the command processor fromdelivering when it is not supposed and also may alarm if the commandprocessor does not deliver when it should be delivering. The supervisorprocessor may deactivate the relay/switch assembly if the commandprocessor actuates the wrong switch, or if the command processor ittries to apply power for too lone.

The supervisor processor may redundantly doing calculations for how muchinsulin should be delivered (i.e., double checking the calculations ofthe command processor). Command processor may decide the deliveryschedule, and the supervisor processor may redundantly check thosecalculations.

Supervisor also redundantly holds the profiles (delivery profiles) inRAM, so the command processor may be doing the correct calculations, butif is has bad RAM, would cause the command to come up with the wrongresult. The Supervisor uses its local copy of the basal profile, etc.,to double check.

Supervisor can double check AVS measurements, looks at the AVScalculations and applies safety checks. Every time AVS measurement istaken, it double checks. Referring also to FIG. 40, one or more ofsupervisor processor 1800 and command processor 1802 may performdiagnostics on various portions of infusion pump assembly 100. Forexample, voltage dividers 1812, 1814 may be configured to monitor thevoltages (V1 & V2 respectively) sensed at distal ends of e.g., shapememory actuator 112. The value of voltages V1 & V2 in combination withthe knowledge of the signals applied to relay/switch assemblies 1804,1810 may allow for diagnostics to be performed on various components ofthe circuit shown in FIG. 40 (in a manner similar to that shown inillustrative diagnostic table 1816).

As discussed above and as illustrated in FIGS. 39-40, to enhance thesafety of infusion pump assembly 100, electrical control assembly 110may include a plurality of microprocessors (e.g., supervisor processor1800 and command processor 1802), each of which may be required tointeract and concur in order to effectuate the delivery of a dose of theinfusible fluid. In the event that the microprocessors fail tointeract/concur, the delivery of the dose of infusible fluid may failand one or more alarms may be triggered, thus enhancing the safety andreliability of infusion pump assembly 100.

A master alarm may be utilized that tracks the volume error over time.Accordingly, if the sum of the errors becomes too large, the masteralarm may be initiated, indicating that something may be wrong with thesystem. Accordingly, the master alarm may be indicative of a totalvolume comparison being performed and a discrepancy being noticed. Atypical value of the discrepancy required to initiate the master alarmmay be 1.00 milliliters. The master alarm may monitor the sum in a leakyfashion (i.e., Inaccuracies have a time horizon).

Referring also to FIGS. 41A-41B, there is shown one such illustrativeexample of such interaction amongst multiple microprocessors during thedelivery of a dose of the infusible fluid. Specifically, commandprocessor 1802 may first determine 1900 the initial volume of infusiblefluid within volume sensor chamber 620. Command processor 1802 may thenprovide 1902 a “pump power request” message to supervisor processor1800. Upon receiving 1904 the “pump power request” message, supervisorprocessor 1800 may e.g., energize 1906 relay/switch 1810 (thusenergizing shape memory actuator 112) and may send 1908 a “pump poweron” message to command processor 1802. Upon receiving 1910 the “pumppower on” message, command processor 1802 may actuate 1912 e.g., pumpassembly 106 (by energizing relay/switch 1804), during which timesupervisor processor 1800 may monitor 1914 the actuation of e.g., pumpassembly 106.

Once actuation of pump assembly 106 is complete, command processor 1802may provide 1914 a “pump power off” message to supervisor processor1800. Upon receiving 1916 the “pump power off” message, supervisorprocessor 1800 may deenergize 1918 relay/switch 1810 and provide 1920 a“pump power off” message to command processor 1802. Upon receiving 1922the “pump power off” message, command processor 1802 may measure 1924the quantity of infusible fluid pumped by pump assembly 106. This may beaccomplished by measuring the current quantity of fluid within volumesensor chamber 620 and comparing it with the quantity determined above(in step 1900). Once determined 1924, command processor 1802 may provide1926 a “valve open power request” message to supervisor processor 1800.Upon receiving 1928 the “valve open power request” message, supervisorprocessor 1800 may energize 1930 relay/switch 1810 (thus energizingshape memory actuator 632) and may send 1932 a “valve open power on”message to command processor 1802. Upon receiving 1934 the “valve openpower on” message, command processor 1802 may actuate 1936 e.g.,measurement valve assembly 610 (by energizing relay/switch 1806), duringwhich time supervisor processor 1800 may monitor 1938 the actuation ofe.g., measurement valve assembly 610.

Once actuation of measurement valve assembly 610 is complete, commandprocessor 1802 may provide 1940 a “valve power off” message tosupervisor processor 1800. Upon receiving 1942 the “valve power off”message, supervisor processor 1800 may deenergize 1944 relay/switch 1810and provide 1946 a “valve power off” message to command processor 1802.

Upon receiving 1948 the “valve power off” message, command processor1802 may provide 1950 a “valve close power request” message tosupervisor processor 1800. Upon receiving 1952 the “valve close powerrequest” message, supervisor processor 1800 may energize 1954relay/switch 1810 (thus energizing shape memory actuator 652) and maysend 1956 a “power on” message to command processor 1802. Upon receiving1958 the “power on” message, command processor 1802 may actuate 1960 anenergizing relay/switch (not shown) that is configured to energize shapememory actuator 652, during which time supervisor processor 1800 maymonitor 1962 the actuation of e.g., shape memory actuator 652.

Shape memory actuator 652 may be anchored on a first end usingelectrical contact 654. The other end of shape memory actuator 652 maybe connected to bracket assembly 656. When shape memory actuator 652 isactivated, shape memory actuator 652 may pull bracket assembly 656forward and release valve assembly 634. As such, measurement valveassembly 610 may be activated via shape memory actuator 632. Oncemeasurement valve assembly 610 has been activated, bracket assembly 656may automatically latch valve assembly 610 in the activated position.Actuating shape memory actuator 652 may pull bracket assembly 656forward and release valve assembly 634. Assuming shape memory actuator632 is no longer activated, measurement valve assembly 610 may move to ade-activated state once bracket assembly 656 has released valve assembly634. Accordingly, by actuating shape memory actuator 652, measurementvalve assembly 610 may be deactivated.

Once actuation of shape memory actuator 652 is complete, commandprocessor 1802 may provide 1964 a “power off” message to supervisorprocessor 1800. Upon receiving 1966 the “power off” message, supervisorprocessor 1800 may deenergize 1968 relay/switch 1810 and may provide1970 a “power off” message to command processor 1802. Upon receiving1972 the “power off” message, command processor 1802 may determine thequantity of infusible fluid within volume sensor chamber 620, thusallowing command processor 1802 to compare this measured quantity to thequantity determined above (in step 1924) to determine 1974 the quantityof infusible fluid delivered to the user.

In the event that the quantity of infusible fluid delivered 1974 to theuser is less than the quantity of infusible fluid specified for thebasal/bolus infusion event, the above-described procedure may berepeated (via loop 1976).

Referring also to FIG. 42, there is shown another illustrative exampleof the interaction amongst processors 1800, 1802, this time during thescheduling of a dose of infusible fluid. Command processor 1802 maymonitor 2000, 2002 for the receipt of a basal scheduling message or abolus request message (respectively). Upon receipt 2000, 2002 of eitherof these messages, command processor 1802 may set 2004 the desireddelivery volume and may provide 2006 a “delivery request” message tosupervisor processor 1800. Upon receiving 2008 the “delivery request”message, supervisor processor 1800 may verify 2010 the volume defined2004 by command processor 1802. Once verified 2010, supervisor processor1800 may provide 2012 a “delivery accepted” message to command processor1802. Upon receipt 2014 of the “delivery accepted” message, commandprocessor 1802 may update 2016 the controller (e.g., the controllerdiscussed above and illustrated in FIG. 33) and execute 2018 delivery ofthe basal/bolus dose of infusible fluid. Command processor 1808 maymonitor and update 2022 the total quantity of infusible fluid deliveredto the user (as discussed above and illustrated in FIGS. 41A-41B). Oncethe appropriate quantity of infusible fluid is delivered to the user,command processor 1802 may provide 2024 a “delivery done” message tosupervisor processor 1800. Upon receipt 2026 of the “delivery done”message, supervisor processor 1800 may update 2028 the total quantity ofinfusible fluid delivered to the user. In the event that the totalquantity of infusible fluid delivered 2018 to the user is less than thequantity defined above (in step 2004), the infusion process discussedabove may be repeated (via loop 2030).

Referring also to FIG. 43, there is shown an example of the manner inwhich supervisor processor 1800 and command processor 1802 may interactwhile effectuating a volume measurements via volume sensor assembly 148(as described above).

Specifically, command processor 1802 may initialize 2050 volume sensorassembly 148 and begin collecting 2052 data from volume sensor assembly148, the process of which may be repeated for each frequency utilized inthe above-described sine sweep. Each time that data is collected for aparticular sweep frequency, a data point message may be provided 2054from command processor 1802, which may be received 2056 by supervisorprocessor 1800.

Once data collection 2052 is completed for the entire sine sweep,command processor 1802 may estimate 2058 the volume of infusible fluiddelivered by infusion pump assembly 100. Command processor 1802 mayprovide 2060 a volume estimate message to supervisor processor 1800.Upon receiving 2062 this volume estimate message, supervisor processor1800 may check (i.e., confirm) 2064 the volume estimate message. Oncechecked (i.e., confirmed), supervisor processor 1800 may provide 2066 averification message to command processor 1802. Once received 2068 fromsupervisor processor 1800, command processor 1802 may set themeasurement status for the dose of infusible fluid delivered by volumesensor assembly 148.

Occlusions and/or leaks may occur anywhere along the fluid delivery pathof infusion pump assembly 100. For example and referring to FIG. 44,occlusions/leaks may occur: in the fluid path between reservoir 118 andreservoir valve assembly 614; in the fluid path between reservoir valveassembly 614 and pump assembly 106; in the fluid path between pumpassembly 106 and volume sensor valve assembly 612; in the fluid pathbetween volume sensor valve assembly 612 and volume sensor chamber 620;in the fluid path between volume sensor chamber 620 and measurementvalve assembly 610; and in the fluid path between measurement valveassembly 610 and the tip of disposable cannula 138. Infusion pumpassembly 100 may be configured to execute one or more occlusion/leakdetection algorithms that detect and locate such occlusions/leaks andenhance the safety/reliability of infusion pump assembly 100.

As discussed above, when administering the infusible fluid, infusionpump assembly 100 may first determine the volume of infusible fluidwithin volume sensor chamber 620 prior to the administration of the doseof infusible fluid and may subsequently determine the volume ofinfusible fluid within volume sensor chamber 620 after theadministration of the dose of infusible fluid. By monitoring thesevalues, the occurrence of occlusions/leaks may be detected.

Occlusion Type—Total: When a total occlusion is occurring, thedifference between the initial measurement prior to the administrationof the dose of infusible fluid and the final measurement after theadministration of the dose of infusible fluid will be zero (oressentially zero), indicating a large residual quantity of infusiblefluid within volume sensor chamber 620. Accordingly, no fluid may beleaving volume sensor chamber 620.

Specifically, if the tip of disposable cannula is occluded, the fluidpath down stream of volume sensor chamber 620 will fill with fluid andeventually become pressurized to a level equivalent to the mechanicalpressure exerted by spring diaphragm 628. Accordingly, upon measurementvalve assembly 610 opening, zero (or essentially zero) fluid will bedispensed and, therefore, the value of the initial and finalmeasurements (as made by volume sensor assembly 148) will essentially beequal.

Upon detecting the occurrence of such a condition, a total occlusionflag may be set and infusion pump assembly 100 may e.g., trigger analarm, thus indicating that the user needs to seek alternative means forreceiving their therapy.

Occlusion Type—Partial: When a partial occlusion is occurring, thedifference between the initial measurement prior to the administrationof the dose of infusible fluid and the final measurement after theadministration of the dose of infusible fluid will indicate that lessthan a complete dose of infusible fluid was delivered. For example,assume that at the end of a particular pumping cycle, volume sensorassembly 148 indicated that 0.10 microliters of infusible fluid werepresent in volume sensor chamber 620. Further, assume that measurementvalue assembly 610 is subsequently closed and pump assembly 106 issubsequently actuated, resulting in volume sensor chamber 620 beingfiled with the infusible fluid. Further assume that volume sensorassembly 148 determines that volume sensor chamber 620 is now filledwith 1.00 microliters of infusible fluid (indicating a pumped volume of0.90 microliters).

Accordingly, upon the opening of measurement valve assembly 610, thequantity of infusible fluid included within volume sensor chamber wouldbe expected to drop to 0.10 microliters (or reasonably close thereto).However, in the event of a partial occlusion, due to aslower-than-normal flow rate from volume sensor chamber 620, thequantity of infusible fluid within volume sensor chamber 620 may only bereduced to 0.40 microliters (indicating a delivered volume of 0.60microliters). Accordingly, by monitoring the difference between thepumped volume (0.90 microliters) and the delivered volume (0.60microliters), the residual volume may be defined and the occurrence of apartial occlusion may be detected.

Upon detecting the occurrence of such a condition, a partial occlusionflag may be set and infusion pump assembly 100 may e.g., trigger analarm, thus indicating that the user needs to seek alternative means forreceiving their therapy. However, as this is indicative of a partialocclusion (as opposed to a complete occlusion), the issuance of an alarmmay be delayed, as the partial occlusion may clear itself.

Alternatively, infusion pump assembly 100 may: calculate a pump ontimeto volume delivered ratio; track it through time; and track by using afast moving and a slow moving exponential average of the pump ontime.The exponential average may be tracked, in a fashion similar to theleaky sum integrator. The infusion pump assembly 100 may filter signaland look for a fast change. The rate of fluid outflow and/or residualvolume may be monitored. If the residual volume does not change, thenthere may be a total occlusion. If the residual volume changed, they maybe a partial occlusion. Alternatively still, the residual values may besummed. If the number of valve actuations or the latch time is beingvaried, the fluid flow rate may be examined, even if you build uppressure in volume sensor assembly 148.

Total/Partial Empty Reservoir: When reservoir 118 is becoming empty, itwill become more difficult to fill volume sensor chamber 620 to thedesired level. Typically, pump assembly 106 is capable of pumping 1.0microliters per millisecond. For example, assume that an “empty”condition for volume sensor chamber 620 is 0.10 microliters and a “full”condition for volume sensor chamber 620 is 1.00 microliters. However, asreservoir 118 begins to empty, it may become harder for pump assembly106 to fill volume sensor chamber 620 to the “full” condition and mayconsistently miss the goal. Accordingly, during normal operations, itmay take one second for pump assembly 106 to fill volume sensor chamber620 to the “full” condition and, as reservoir 118 empties, it may takethree seconds to fill volume sensor chamber 620 to the “full” condition.Eventually, if reservoir 118 completely empties, volume sensor chamber620 may never be able to achieve a “full condition”. Accordingly, theinability of pump assembly 106 to fill volume sensor chamber 620 to a“full” condition may be indicative of reservoir 118 being empty.Alternatively, the occurrence of such a condition may be indicative ofother situations (e.g., the failure of pump assembly 106 or an occlusionin the fluid path prior to volume sensor chamber 620). Infusion pumpassembly 100 may determine the difference between the “full” conditionand the amount actually pumped. These differences may be summed and themade up for once the reservoir condition is addressed.

Upon detecting the occurrence of such a condition, an empty flag may beset and infusion pump assembly 100 may e.g., trigger an alarm, thusindicating that the user needs to e.g., replace disposable housingassembly 114.

Additionally, as reservoir 118 empties, reservoir 118 will eventuallyresult in a “vacuum” condition and the ability of pump assembly 106 todeliver fluid to volume sensor chamber 620 may be compromised: Asdiscussed above, volume controller 1602 may include feed forwardcontroller 1652 for setting an initial “guess” concerning “on-time”signal 1606, wherein this initial guess is based upon a pump calibrationcurve. For example, in order for pump assembly 106 to deliver 0.010units of infusible fluid, feed forward controller 1652 may define aninitial “on-time” of e.g., one millisecond. However, as reservoir 118begins to empty, due to compromised pumping conditions, it may take twomilliseconds to deliver 0.010 units of infusible fluid. Further, asreservoir 118 approaches a fully empty condition, it make take tenmilliseconds to deliver 0.010 units of infusible fluid. Accordingly, theoccurrence of reservoir 118 approaching an empty condition may bedetected by monitoring the level at which the actual operation of pumpassembly 106 (e.g., two milliseconds to deliver 0.010 units of infusiblefluid) differs from the anticipated operation of pump assembly 106(e.g., one millisecond to deliver 0.010 units of infusible fluid).

Upon detecting the occurrence of such a condition, a reserve flag may beset and infusion pump assembly 100 may e.g., trigger an alarm, thusindicating that the user will need to e.g., replace disposable housingassembly 114 shortly.

Leak Detection: In the event of a leak (e.g., a leaky valve or arupture/perforation) within the fluid path, the ability of the fluidpath to retain fluid pressure may be compromised. Accordingly, in orderto check for leaks within the fluid path, a bleed down test may beperformed in which pump assembly 106 is used to pressurize volume sensorchamber 620. Volume sensor assembly 148 may then perform a first volumemeasurement (as described above) to determine the volume of infusiblefluid within volume sensor chamber 620. Infusion pump assembly 100 maythen wait a defined period of time to allow for bleed down in the eventof a leak. For example, after a sixty second bleed down period, volumesensor assembly 148 may perform a second volume measurement (asdescribed above) to determine the volume of infusible fluid withinvolume sensor chamber 620. If there are no leaks, the two volumemeasurements should be essentially the same. However, in the event of aleak, the second measurement may be less then the first measurement.Additionally, depending on the severity of the leak, pump assembly 106may be incapable of filling volume sensor chamber 620. Typically, a leakcheck may be performed as part of a delivery of infusible fluid.

In the event that the difference between the first volume measurementand the second volume measurement exceeds an acceptable threshold, aleak flag may be set and infusion pump assembly 100 may e.g., trigger analarm, thus indicating that the user needs to seek alternative means forreceiving their therapy

Referring to FIG. 45 and FIG. 46, an exemplary embodiment of a splitring resonator antenna adapted for use in a wirelessly controlledmedical device, and is used. in the exemplary embodiment of the infusionpump assembly, includes at least one split ring resonator antenna(hereinafter “SRR antenna”) 2508, a wearable electric circuit, such as awirelessly controlled medical infusion apparatus (hereinafter “infusionapparatus”) 2514, capable of powering the antenna, and a control unit2522.

In various embodiments, a SRR antenna 2508 may reside on the surface ofa non-conducting substrate base 2500, allowing a metallic layer (orlayers) to resonate at a predetermined frequency. The substrate base2500 may be composed of standard printed circuit board material such asFlame Retardant 2 (FR-2), FR-3, FR-4, FR-5, FR-6, G-10, CEM-1, CEM-2,CEM-3, CEM-4, CEM-5, Polyimide, Teflon, ceramics, or flexible Mylar. Themetallic resonating bodies comprising a SRR antenna 2508 may be made oftwo rectangular metallic layers 2502, 2504, made of for example,platinum, iridium, copper, nickel, stainless steel, silver or otherconducting materials. In other various embodiments, a SRR antenna 2508may contain only one metallic resonating body.

In the exemplary embodiment, a gold-plated copper outer layer 2502,surrounds, without physically contacting, a gold-plated copper innerring 2504. That is, the inner ring 2504 resides in the cavity 2510 (oraperture) formed by the outer layer 2502. The inner ring 2504 maycontain a gap, or split 2506, along its surface completely severing thematerial to form an incomplete ring shape. Both metallic resonatingbodies 2502, 2504 may reside on the same planar surface of the substratebase 2500. In such a configuration, the outer layer 2502 may by drivenvia a transmission line 2512 coupled to the outer layer 2502, forexample. Additionally, in various other embodiments, a transmission line2512 may be coupled to the inner ring 2504.

Antenna design software, such as AWR Microwave Office, capable ofsimulating electromagnetic geometries, such as, antenna performance, maysignificantly decrease the time required to produce satisfactorydimensions compared to physically fabricating and testing antennas.Accordingly, with aid of such software, the SRR antenna 2508 may bedesigned such that the geometric dimensions of the resonant bodies 2502,2504 facilitate an operational frequency of 2.4 GHz. FIG. 50 depicts theexemplary dimensions of the inner ring 2504 and outer layer 2502, andthe positioning of the cavity 2510 in which the inner ring 2504 resides.The distance in between the outer layer 2502 and the inner ring 2504 isa constant 0.005 inches along the perimeter of the cavity 2510. However,in other embodiments, the distance between the outer layer and the innerring may vary and in some embodiments, the operational frequency mayvary.

In various embodiments, a SRR antenna 2508 may have dimensions such thatit could be categorized as electrically small, that is, the greatestdimension of the antenna being far less than one wavelength atoperational frequency.

In various other embodiments, a SRR antenna 2508 may be composed of oneor more alternatively-shaped metallic outer layers, such as circular,pentagonal, octagonal, or hexagonal, surrounding one or more metallicinner layers of similar shape. Further, in various other embodiments,one or more metallic layers of a SRR antenna 2508 may contain gaps inthe material, forming incomplete shapes:

Referring to FIG. 48, a SRR antenna 2508 having the exemplary geometryexhibits acceptable return loss and frequency values when placed incontact with human skin. As shown in FIG. 48, focusing on the band ofinterest denoted by markers 1 and 2 on the graph, return loss prior tocontact with human skin is near −15 dB while monitoring a frequency bandcentered around 2.44 GHz. Return loss during contact with human skin, asshown in FIG. 48A, remains a suitable value near −25 dB at the samefrequency, yielding approximately 97% transmission power.

These results are favorable especially as compared with a non-split ringresonator antenna type, such as the Inverted-F. Return loss of anInverted-F antenna may exhibit a difference when the antenna contactshuman skin, resulting in a low percentage of power transmitted outwardfrom the antenna. By way of example, as shown in FIG. 51, and againfocusing on the band of interest denoted by markers 1 and 2 on thegraph, return loss of an Inverted-F antenna prior to contact with humanskin is near −25 dB at a frequency centered around 2.44 GHz. Return lossduring contact with human skin is nearly −2 dB at the same frequency,yielding approximately 37% power transmission.

Integration with a Wireless Medical Device

In the exemplary embodiment, referring to FIG. 50 and FIG. 46, oneapplication of a SRR antenna 2508 may be integration into a wearableinfusion apparatus 2514 capable of delivering fluid medication to auser/patient 2524. In such an application, the safety of theuser/patient is dependent on fluid operation between these electricalcomponents, thus reliable wireless transmission to and from a controlunit 2522 is of great importance.

An infusion apparatus 2514 may be worn directly on the human body. Byway of example, such a device may be attached on or above the hip jointin direct contact with human skin, placing the SRR antenna 2508 at riskof unintended dielectric loading causing a frequency shift in electricaloperation. However, in such an application, electrical characteristicsof the SRR antenna 2508 which allow it to be less sensitive to nearbyparasitic objects are beneficial in reducing or eliminating degradationto the performance. A controlling component, such as a Control unit 2522(generally shown in FIG. 49), may be paired with an infusion apparatus2514, and may be designed to transmit and receive wireless signals toand from the infusion apparatus 2514 at a predetermined frequency, suchas 2.4 GHz. In the exemplary embodiment, the control unit 2522 serves asthe main user interface through which a patient or third party maymanage insulin delivery. In other embodiments, infusion apparatus 2514may utilize a SRR antenna 2508 to communicate with one or more controlunits 2522.

In various embodiments, a number of different wireless communicationprotocols may be used in conjunction with the SRR antenna 2508, as theprotocol and data types to be transferred are independent of theelectrical characteristics of the antenna. However, in the exemplaryembodiment, a bi-directional master/slave means of communicationorganizes the data transfer through the SRR antenna 2508. The controlunit 2522 may act as the master by periodically polling the infusionapparatus 2514, or slave, for information. In the exemplary embodiment,only when the slave is polled, the slave may send signals to the controlunit 2522 only when the slave is polled. However, in other embodiments,the slave may send signals before being polled. Signals sent by way ofthis system may include, but are not limited to, control, alarm, status,patient treatment profile, treatment logs, channel selection andnegotiation, handshaking, encryption, and check-sum. In someembodiments, transmission through the SRR antenna 2508 may also behalted during certain infusion operations as an added precaution againstelectrical disruption of administration of insulin to the patient.

In the exemplary embodiment, the SRR antenna 2508 may be coupled toelectrical source circuitry via one or more pins 2516 on a transmissionline 2512. In various other embodiments a transmission line may comprisea wire, pairs of wire, or other controlled impedance methods providing achannel by which the SRR antenna 2508 is able to resonate at a certainfrequency. The transmission line 2512 may reside on the surface of thesubstrate base 2500 and may be composed of the same material as the SRRantenna 2508, such as gold-plated copper. Additionally, a ground planemay be attached to the surface of the substrate base opposite thetransmission line 2512.

The electrical circuitry coupled to the SRR antenna 2508 may apply an RFsignal to the end of the transmission line 2512 nearest the circuitry,creating an electromagnetic field throughout, and propagating from, theSRR antenna 2508. The electrical circuitry coupled to the SRR antenna2508 facilitates resonance at a predetermined frequency, such as 2.4GHz. Preferably, transmission line 2512 and SRR antenna 2508 both haveimpedances of 50 Ohms to simplify circuit simulation andcharacterization. However, in other various embodiments, thetransmission line and split ring resonator antenna may have otherimpendence values, or a different resonating frequency.

Referring to FIG. 47, a signal processing component(s) 2518, such as, afilter, amplifier, or switch, may be integrated into the transmissionline 2512, or at some point between the signal source connection pins2516 and the SRR antenna 2508. In the exemplary embodiment, the signalprocessing component 2518 is a band-pass filter to facilitate desiredsignal processing, such as, allowing only the exemplary frequency to betransmitted to the antenna, and rejecting frequencies outside thatrange. In the exemplary embodiment, a Combine band-pass filter 2518 maybe included in the transmission line 2512 between the antenna and thesignal source. However in other embodiments, any other signal processingdevice, for example, but not limited to, filters, amplifiers, or anyother signal processing devices known in the art.

In various embodiments, a SRR antenna 2508 may be composed of metallicbodies capable of resonating on a flexible or rigid substrate. As shownin FIG. 46, the exemplary embodiment incorporates a curved SRR antennaon a flexible Polyimide substrate 2520.

Polyimide may be the exemplary material because it tends to be moreflexible than alternative substrates. This configuration may allow forsimplified integration into circular-shaped devices (such as awirelessly controlled medical infusion apparatus 2514), devices withirregular-shaped external housing, or devices in which saving space isparamount.

In various embodiments, both control unit 2522 and base unit 2514 mayincorporate a split SRR antenna 2508. This configuration may provebeneficial where the control unit is meant to be handheld, in closeproximity to human skin, or is likely to be in close proximity to avarying number of materials with varying dielectric constants.

In various embodiments, a SRR antenna 2508 may be integrated into aconfiguration of medical components in which one or more implantablemedical devices, operating within the human body, communicate wirelesslyto a handheld, body-mounted, or remote control unit. In certainembodiments, both body-mounted and in-body wireless devices may utilizea SRR antenna 2508 for wireless communication. Additionally, one or moreof the components utilizing a SRR antenna 2508 may be completelysurrounded by human skin, tissue or other dielectric material. By way ofexample, such a configuration may be used in conjunction with a heartmonitoring/control system where stability and consistency of wirelessdata transmission are of fundamental concern.

In various other embodiments, a SRR antenna 2508 may be integrated intothe embodiments of the infusion pump assembly. Configuration of medicalcomponents in which one or more electrical sensors positioned on, orattached to, the human body wirelessly communicate to a remotetransceiving unit. By way of example, a plurality of electrodespositioned on the body may be coupled to a wireless unit employing a SRRantenna 2508 for wireless transmission to a remotely locatedelectrocardiogram machine. By way of further example, a wirelesstemperature sensor in contact with human skin may employ SRR antenna2508 for wireless communication to a controller unit for temperatureregulation of the room in which the sensor resides.

The infusion pump described herein contains a NITINOL, or shape-memoryalloy, actuated binary valve (the measurement valve). This valve isactuated by applying an electrical current to the NITINOL wire whichcauses the wire to change phase, contract, and actuate the valve. It isdesirable to minimize the time that current is applied to the NITINOLfor many reasons, including, but not limited to, the following: 1) tominimize power consumption; 2) to minimize cycle time; and 3) tomaximize NITINOL cycle life. Minimizing power consumption may extend thebattery life and thus, provide for longer functionality of the pumpbetween recharging. Maximizing the NITINOL cycle life extends the lifeof the resusable portion of the infusion pump and provides for longerperformance of the pump. Both of these may be desirable in a closed-loopor semi-closed loop system, as well as in an open loop system.

Regular operation of the pump involves the following steps, amongstothers. First, an initial volume measurement is taken of the AcousticVolume Sensor chamber using the Acoustic Volume Sensor (AVS). Next,fluid is pumped from the reservoir to the AVS chamber using the pulsepump. Then, another measurement is taken of the full AVS chamber. Next,the measurement valve is actuated and the fluid released from the AVSchamber and to the user/patient through a tubing set. Finally, a finalAVS measurement is taken.

In various embodiments, the difference between the second and first AVSmeasurements is the pumped volume; this is the volume pumped into theAVS chamber. The difference between the second and the third AVSmeasurements is the delivered volume; this is the volume delivered tothe user/patient. The difference between the pumped volume and thedelivered volume is the residual volume; this is the volume remaining inthe AVS chamber after the actuation of the measurement valve.

The measurement valve is actuated by allowing current to flow throughthe Valve NITINOL wire at a given duty cycle and on-time. In theexemplary embodiments the valve may be driven at a nominal 8% duty cyclethat is adjusted to compensate for variations in supply voltage. In theexemplary embodiments, the ontime that is varied to minimize theelectrical power used to actuate the valve. However, in otherembodiments, a similar result may be accomplished by varying the dutycycle instead of the ontime or by using a combination of the two, forexample. The ontime is varied using the algorithm described below.

When the controller is initialized the valve ontime, t_(on), isinitially set to a low value that is below the minimum ontime needed toactuate the valve (which, in some embodiments, is approximately 200 ms).Deliveries are conducted using the steps #1 to #5 described above. Whenthese steps are complete the following additional steps are taken. Theresidual volume is calculated; if the residual volume is not close tozero, it is likely that the valve did not open. In this case t_(on) isincreased (in the exemplary embodiment, the t_(on) is increased by afixed 20 ms each iteration, however, in other embodiments, the increaseontime may vary) and steps #4 to #7 are repeated until the valve opensand either the residual volume is close to zero or the maximum allowedvalve ontime is reached.

This algorithm effectively increases the valve ontime by just enough (towithin the on-time increment) to open the valve. However, it is possiblethat the necessary on-time may decrease over time or may be abnormallyhigh during a given delivery. If this were the case the valve ontimewould increase to compensate, but would then remain high until thecontroller/algorithm is reset. In the exemplary embodiments, determiningwhether the AVS valve was actuated for longer than necessary may not becompleted. Thus, in some embodiments, to compensate for this nondetermination, once the valve opens, the residual volume will be closeto zero regardless of any extra open time. The valve controller thendecrements the valve ontime each delivery (in the exemplary embodiment,the decrease is by 2 ms, however, in other embodiments, this decreaseamount may be different). This allows the valve ontime to graduallydecrease until it is insufficient to open the valve. At that point thealgorithm described above will increase the valve ontime by a largerincrement (e.g., 20 ms) and the process will continue. The result is acontrol profile of valve ontimes close to the minimum value needed toopen the valve. In these embodiments, the system uses the minimum amountof power to actuate the measurement valve.

In exemplary embodiments, and referring to the controller describedabove, volume sensor assembly monitors the amount of fluid infused bythe infusion pump assembly. Thus, following the infusion of fluid fromthe volume sensor chamber, the controller determines whether the volumeinfused is less than or greater than the desired volume or scheduledvolume for that pulse. Following, the controller may either increase ordecrease the volume delivered in a pulse, or over a series of pulses,following. This includes, but is not limited to, the controller addingor subtracting a volume from one or more pulse of upcoming scheduleddelivery volumes for a given period of time. Thus, embodiments of thefluid delivery system include a controller that both calculates thevolume of infusible fluid delivered and also, recalculates, asnecessary, upcoming delivery volumes based on the volume delivered inany given pulse. This ensures the desired volume is delivered within ashort period of time from any given pulse.

As discussed above, with reference to the delivery of insulin forpurposes of illustration, various delivery volumes may be eitherprogrammed or requested at a given time. These include, but are notlimited to, a normal bolus, an extended bolus, a combination bolus(i.e., a percentage of an extended bolus delivered as a normal bolus,followed by the remaining percentage delivered over a desired/requestedor pre-determined period of time), and a basal rate (which, in manyembodiments, may include one or more pre-programmed basal rates per a 24hour period).

The system for controlling the delivery of infusible fluid includes adelivery trajectory, i.e., volumes of fluid, whether basal, normalbolus, extended bolus, and/or combination bolus, which will be delivery,as well as a schedule, i.e., when the various volumes will be delivered.As discussed above, in the exemplary embodiments, the controllerincludes a feedback mechanism. Thus in some embodiments, the trajectoryand the schedule for delivery may vary based on the volume sensorassembly measured volumes.

In the exemplary embodiments, a constant, or approximately constant,trajectory may be beneficial. A constant trajectory may be desired formany reasons, including, but not limited to, maintaining a constanttrajectory to eliminate or mitigate transience. Transience may beintroduced into the system based on the mapping of the joules applied tothe shape-memory actuator and the resulting volume delivered or measuredby the volume sensor assembly. Over time, the mapping may vary.Contributing factors that may vary the mapping include, but are notlimited to, temperature, reservoir volume, and/or time and use of theshape-memory actuator. Thus, it may be desirable to maintain a close toconstant trajectory in order to eliminate the influence of variableswhich may be introduced and/or may affect the system. Additionally, aconstant trajectory gives rise to further opportunities for thecontroller to adjust delivery volumes in response to volume sensorassembly measurements.

In various embodiments of this delivery method and system, a trajectoryis calculated based on delivery commands the system receives, which mayinclude e.g., bolus, extended bolus, combination bolus and basal. Theinterval for delivery may be determined based on one or more of thefollowing factors: 1) the maximum pulse volume; 2) the minimal pulsevolume; 3) power consumption; and/or 4) minimum pulse interval. In theexemplary embodiment, one or more factors may be taken intoconsideration. In various embodiments the system determines thetrajectory, and working within the confines of the interval factors,determines the interval and volume of fluid delivery to meet the desiredtrajectory, with the preference, in some embodiments, that each deliverybe of an equal volume and that the delivery be completed in as manyequal volume deliveries as possible (to allow for adjustments in thevolume). Thus, the intervals may vary, but in the exemplary embodiment,the volumes delivered per interval will be constant, or approachingconstant.

In the exemplary embodiment, with respect to bolus delivery, whendetermining the interval for delivery of the bolus volume, the systemmay determine the delivery schedule for the bolus volume to be deliveredas quickly as possible within system preferences (i.e., values that mayoptimize the system performance) and/or system constraints (i.e.,minimum and maximum pulses and minimum and maximum intervals). Forexample, in the exemplary embodiment, the system may include a maximumpulse delivery volume of 2.0 microliters and a minimum pulse deliveryvolume of 0.5 microliters. Further, in some embodiments, it may bepreferred that the minimum pulse interval is six (6) minutes. Thus,given the maximum and minimum pulse volume, together with the minimuminterval, the system may determine the optimal schedule for delivery,i.e., the volume of each delivery (with the preference being that eachscheduled volume is equal) and the interval between each delivery.

In some embodiments, in determining the number of deliveries for a bolusvolume, the system may defer to delivering the bolus volume as quicklyas possible, given that each scheduled pulse for the bolus delivery isequal. However, in some embodiments, the system may determine the numberof deliveries for a bolus volume by deferring to a set number of pulses,e.g., ten (10). Given this deference, the system may then determine theintervals and volume of each pulse by dividing the bolus volume by 10.Following, if the resulting delivery volume is less than the minimumdelivery volume, e.g., 0.5 microliters, then the system may determinethe schedule based on less than 10 pulses. If the resulting deliveryvolume is greater than the maximum delivery volume, e.g., 2.0microliters, the system may determine the schedule based on more than 10pulses. Thus, although in the exemplary embodiment, the system may givedeference to a given number of pulses to deliver a requested volume, thesystem may decrease or increase that given number of pulses if thevolumes are less than the minimum pulse volume, or greater than themaximum pulse volume. It should be noted that although exemplaryembodiments have been described, this is for illustrative purposes only.In other embodiments, the system may have a different deference numberfor the number of pulses, and/or difference values for minimum andmaximum pulse volumes. Further, the exemplary interval may also vary,thus, in some embodiments, the preferred interval may be less than 6minutes or greater than 6 minutes.

As discussed above, in addition to bolus scheduling, other deliveriesintervals, e.g., extended bolus, combination bolus and basal, may alsobe determined with the desire that each pulse volume is equal. Thus, theintervals may vary: however, as discussed above, the system may includea minimum interval, e.g., 6 minutes. With respect to scheduling basaldeliveries, in the exemplary embodiment, the schedule for a given basalrate delivery may be determined by first dividing the rate per hour by apreferred interval (e.g., 6 minutes). For example, with a rate of 1 unit(i.e., in terms of U-100 insulin, 10 microliters) per hour, the schedulemay be 1 delivery of 1.0 microliter every 6 minutes, equating to 10deliveries of 1.0 microliter in one hour. As discussed above, in variousembodiments, the system may include a volume per pulse maximum andminimum, thus, similarly to example given above with respect to bolusrate scheduling, where the volume minimum or maximum is reached, thenumber of pulses may be increased or decreased accordingly, in order tomaintain equal volume per pulse. An example of a basal rate trajectoryas well as an example of a delivery schedule for that trajectory isshown in FIGS. 53A-53B.

Further to the embodiments of the delivery system and method describedherein, where one or more delivery events are desired for a given timeinterval, i.e., during regular basal delivery, a bolus is requested,this embodiment of the scheduling is beneficial for many reasons,including, but not limited to, determining the volume attributed tobasal and the volume attributed to bolus for purposes of othercalculations, e.g., “insulin on board” calculations. With respect tosome embodiments of this exemplary embodiment, when a basal trajectoryand scheduled delivery are in progress and a bolus is requested, thesystem may calculate the bolus schedule and then recalculate the basalschedule. For example, in some cases, for a single pulse, a portion ofthe pulse volume may be attributed to the “bolus” and a portion to the“basal”, and for a given bolus delivery, together with an ongoing basal,the pulses may deliver equal volumes.

With respect to an extended bolus delivered together with a basal rate,a similar delivery schedule may be calculated. Referring now to FIGS.54A-54B, an example of a basal and extended bolus trajectory and adelivery schedule for that trajectory, are shown. The basal and extendedbolus delivery schedule may be determined by taking into account thetimeframe for the extended bolus and the overlapping rate for any basal.Unlike a normal bolus, in the exemplary embodiment, it may not be thegoal of the system to deliver the extended bolus “as quickly aspossible” given the system constraints, but rather, is delivered over agiven period of time. Thus, the delivery schedule may be determined byfirst calculating the optimal schedule for delivery of the extendedbolus, and then recalculating the basal delivery for the timeframe ofthe extended bolus, such that the basal and extended bolus may bedelivered in equal volume pulses over the timeframe for the extendedbolus.

Referring now to FIGS. 55A-55B, an example of a basal, extended bolusand bolus trajectory and a delivery schedule for that trajectory, areshown. Combining the discussion above regarding scheduling the deliveryof a basal, a normal bolus, and an extended bolus, when all three are tobe delivered during an overlapping time period, FIGS. 55A-55B are anexample of a resulting schedule according to an exemplary embodiment. Asshown, the basal and extended bolus may be delivered at a first intervalwhile the normal bolus may be delivered at a second interval, howevereach of the first and the second intervals include equal deliveryvolumes.

Referring again to FIGS. 54A-54B and FIGS. 55A-55B, it may be understoodthat the system may differentiate a volume delivered as a “basal” from avolume delivered as a “bolus” (including an extended bolus) even whenthe combined volumes are delivered in a single pulse of equal volumesover an overlapping timeframe. This differentiation may be beneficial incalculating the amount of bolus or basal “on board”, i.e., the time atwhich a particular volume of “basal” as opposed to a particular volumeof “bolus” was a delivered in FIGS. 54B and 55B allow for a moreaccurate calculation of insulin on board, as insulin on board is acalculation that depends on many factors, including the time and volumeof delivery.

Various embodiments of the system may include various control-loopalgorithms for either a closed-loop or semi-closed loop control method.In some embodiments, the system includes a baseline trajectory. Asdiscussed above, the system may follow this trajectory until one or moresensor data dictate that the trajectory may change. In some embodiments,the changes to the trajectory may be governed by boundaries which may bepreprogrammed by the user/care giver. As discussed above, changes to thetrajectory, in some embodiments, may be made upon notification to theuser and in some embodiments, upon notification followed by confirmationby the user. In some embodiments, where the trajectory change may be inresponse to unexpected results, the system may notify the user prior toshutting the system down.

Thus, in the various embodiments, control loop algorithms take intoaccount a physiological model (which may be adaptive from a baselinemodel); data from at least one sensor, e.g., a CGM system, i.e.,representing the interstitial fluid glucose level; and the volume ofmedical fluid, e.g. insulin, delivered and fingersticks, i.e.,representing the blood glucose level.

In various embodiments, an estimator works together with a controller.The controller determines the amount of medical fluid or insulin todeliver based on the estimator's prediction. Thus, errors in theestimator will provide for incorrect delivery requests from thecontroller.

More importantly, incorrect amounts delivered by the controller (i.e.,the controller requests a delivery of 0.250 units and actually delivers0.20 or 0.30 or another volume, either higher or lower than the volumerequested) will then alter the effect of the estimator.

In various embodiments, the estimator works with the physiology toestablish a “trajectory”. The trajectory may be based on a number offactors and may be continuously updated/changed. The trajectory uses theCGM data (which may be checked or calibrated by fingersticks asdiscussed herein) and, in some embodiments, an established normalized or“baseline” basal delivery schedule, to predict 1) glucose values and 2)determine delivery volumes and schedule.

As discussed above, the trajectory may be constantly updated or changedbased on actual CGM or fingerstick data (fingerstick data may be used toconfirm CGM data or calibrate the CGM data) and actual volume of insulindelivered. Thus, in a controlled loop or semi-controlled loop system,both the data from the CGM/fingersticks and the actual volume of insulindelivered are key components to the system. Hone or both of these valuesare inaccurate, the system may not perform as effectively as desired.

In some embodiments, using a pre-established or “baseline” deliverytrajectory, the pre-established trajectory may be referred to as an“outer loop”, as the trajectory may include a basic “baseline” deliveryschedule (volume and time of delivery). The trajectory may beestablished using one or more limitations of the hardware, including,but not limited to: the minimum and/or maximum stroke of the pump;optimal delivery patterns; and/or energy efficiency, i.e., battery life.

The actual trajectory may be modified in response to detected meals oran input indicating the presence of a factor or an “event” that mayaffect insulin sensitivity, including, but not limited to, one or moreinputs (either via manual user input or sensor data) indicating exercise(including duration and level or type), illness, dehydration, sleep,menstration and/or stress. Additionally, a meal or carbohydrate beingconsumed by the user is also an event which may affect or alter thetrajectory. As discussed above, through calibration and profile records,and/or through sensor data, the system may predict one or more of theseevents.

Using the actual volume delivered as the input to the estimator mayachieve an accurately met trajectory. Additionally, using the actualvolume delivered may result in a more accurate and precise predicativealgorithm. For example, if the controller requested an insulin deliveryand the actual volume delivered is different from the requested volumeor assumed volume delivered, then the predictive algorithm may beinaccurate. Thus, it is desirable that the trajectory or outer loopitself is as close to correct for the duration as possible, however,even where the trajectory is correct, where the pump fails to deliveryeither the volume desired or at the time desired, the trajectory is notmet. This is an example of the actual trajectory varying from thetrajectory requested or the outer loop.

Thus, the actual delivery versus the trajectory may be very differentwhere the volume delivered by the pump is inaccurate or varies fromrequested. Inaccurate delivery may be the result of pump error,occlusion and/or bubbles in the fluid line, or other. In the exemplaryembodiments, the system uses the AVS sensor and the methods describedherein to accurately and precisely measure the volume of insulindelivered by the pump.

The ability to precisely and accurately determine the volume of insulindelivered effects many aspects of the control loop system. Asnon-limiting example, the precise and accurate determination of volumeof insulin delivered feeds into the precise and accurate determinationof insulin-on-board or “IOB”. The precise estimation or determination ofIOB is a factor with respect to 1) accounting for delivery; and 2)accurate delivery.

Also, in the various embodiments described herein, an accuratemeasurement of the volume of medical fluid/insulin delivered may alsoallow for more accurate and precise recognition of sensor failure or theintegrity failure of one or more sensors. For example, with respect toone or more CGM sensors, if an e.g. 2 unit delivery of insulin wasrequested and the control system assumes the pump delivered 2 units andfollowing, receives glucose data indicating an unexpected result, asdiscussed above, the system, in some embodiments, may instigate defaultshutdown. Thus, the system would shutdown based on the “unexpected” CGMdata. However, assume that the pump actually delivered 1 unit, ratherthan 2 units, and assume that the glucose data is consistent with a 1unit delivery, then the CGM sensor has not produced an actual unexpectedresult, rather, it was a perceived unexpected result based on a lowerthan expected volume of insulin being delivered. Thus, the precise andaccurate determination of the volume of insulin (or other medical fluid)delivered may provide a more accurate and safe controlled loop systemfor the delivery of medical fluid therapy.

Further, with respect to the various embodiments described herein usingthe AVS measurement sensor, the presence of occlusions, bubbles and anempty or partially empty reservoir may be determined quickly andaccurately. Again, this provides for a more accurate determination ofthe actual volume of insulin delivered and, also, an accurate detectionof an empty reservoir, an occlusion or a bubble. Thus, the AVSmeasurement sensor provides for a more safe and accurate controlled loopsystem for the delivery of medical fluid therapy. Further, determiningthe presence of an occlusion, bubble(s), or an empty or partially emptyreservoir may be highly beneficial to the user's therapy and safety.

The precise determination of the volume of insulin delivered alsoeffects the calibration of the system. Thus, having a precisemeasurement, the system may more accurately calibrate and thus, maydetermine unexpected results of integrity failure sooner.

Thus, various embodiments of the control loop include an actual volumeand the trajectory volume. Where a system includes an actual volume thatis closest to the trajectory volume, the estimate of plasma and ISG iscloser to true. This may lead to more accurate insulin sensitivitydeterminations and calculations and more accurate predictive algorithms.

While the principles of the invention have been described herein, it isto be understood by those skilled in the art that this description ismade only by way of example and not as a limitation as to the scope ofthe invention. Other embodiments are contemplated within the scope ofthe present invention in addition to the exemplary embodiments shown anddescribed herein. Modifications and substitutions by one of ordinaryskill in the art are considered to be within the scope of the presentinvention.

1. A system for at least partial closed-loop control of a medicalcondition, the system comprising: at least one medical fluid pump, themedical fluid pump comprising a sensor for determining the volume offluid pumped by the pump; at least one continuous analyte monitor; and acontroller, the controller in communication with the medical fluid pumpand the at least one continuous analyte monitor, the controllercomprising a processor, the processor comprising instructions fordelivery of medical fluid based at least on data received from the atleast one continuous analyte monitor.
 2. The system of claim 1 whereinthe sensor further comprising an acoustic volume sensor.
 3. The systemof claim 1 further comprising a network operation center, the networkoperation center in communication with the processor.
 4. The system ofclaim 1 wherein the pump further comprising: a pumping chamber having aninlet connectable to provide fluid communication with a fluid source,and a pump outlet; and a force application assembly adapted to provide acompressive stroke to the pumping chamber, wherein the compressivestroke causes a restriction of retrograde flow of fluid from the pumpingchamber through the inlet while urging fluid from the pumping chamber tothe pump outlet.
 5. The system of claim 4 further comprising wherein theforce application assembly is coupled to an inlet valve actuator and toa pump actuator, so that the compressive stroke actuates an inlet valvecoupled between the inlet and the fluid source to close the valve whenthe pump actuator causes fluid to be urged from the pumping chamber tothe pump outlet.
 6. The system of claim 5 further comprising wherein theforce application assembly comprising a motor for coordinated operationof the valve actuator and the pump actuator, wherein the motor includesat least one shape-memory actuator.
 7. The system of claim 1 wherein atleast one of the continuous analyte monitors is a continuous glucosemonitor.
 8. The system of claim 1 further comprising at least oneaccelerometer.
 9. The system of claim 1 further comprising at least oneblood oxygen sensor.
 10. The system of claim 1 further comprising atleast one inertial measurement unit comprising at least oneaccelerometer and at least one gyroscope.
 11. The system of claim 1further comprising at least one temperature sensor.
 12. A method for atleast partial closed-loop control of a medical condition, the methodcomprising: receiving glucose data during a time frame or an event;comparing the glucose data to a previous and similar time frame orevent; determining an unexpected result during the time frame or theevent; and sending an alert signal to indicate an unexpected result. 13.The method of claim 12 further comprising wherein sending an alertsignal comprising alerting a user of the unexpected result.
 14. Themethod of claim 13 further comprising prompting the user to enterinformation regarding the unexpected result.
 15. The method of claim 14further comprising wherein the system not receiving informationregarding the unexpected result from the user, shutting down the system.16. The method of claim 15 further comprising wherein shutting down thesystem comprising alerting the user of the shutdown through a series ofalarms.
 17. The method of claim 16 further comprising wherein alertingthe user of the shutdown through a series of alarms comprising alertingthe user of the shutdown through a series of increasing alarms.
 18. Amethod for at least partial closed-loop control of a medical condition,the method comprising: receiving medical fluid delivery data during atime frame or an event; comparing the medical fluid delivery data to aprevious and similar time frame or event; determining an unexpectedresult during the time frame or the event; and sending an alert signalto indicate an unexpected result.
 19. The method of claim 18 furthercomprising wherein sending an alert signal comprising alerting a user ofthe unexpected result.
 20. The method of claim 19 further comprisingprompting the user to enter information regarding the unexpected result.21. The method of claim 20 further comprising wherein the system notreceiving information regarding the unexpected result from the user,shutting down the system.
 22. The method of claim 21 further comprisingwherein shutting down the system comprising alerting the user of theshutdown through a series of alarms.
 23. The method of claim 22 furthercomprising wherein alerting the user of the shutdown through a series ofalarms comprising alerting the user of the shutdown through a series ofincreasing alarms.
 24. A method for monitoring the integrity of ananalyte sensor, the method comprising: injecting a volume of an analytehaving a predetermined concentration in close proximity to a continuousanalyte sensor for the analyte; receiving data from the continuousanalyte sensor; and analyzing the data to determine whether the analytesensor is responsive to the injected volume of analyte.
 25. The methodof claim 24 further comprising wherein the analyte is glucose.